Maturity Model Based on a Suitability Approach for the Evaluation of Chatbots Used in Depression Detection
Descripción del Articulo
In the field of psychology, the use of artificial intelligence-based depression detection chatbots is being employed in order to reduce the percentage of people with depression in the world. However, 3 out of 8 sessions conducted to these software products are not completed due to lack of confidence...
Autores: | , , |
---|---|
Formato: | artículo |
Fecha de Publicación: | 2024 |
Institución: | Universidad Peruana de Ciencias Aplicadas |
Repositorio: | UPC-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorioacademico.upc.edu.pe:10757/676323 |
Enlace del recurso: | http://hdl.handle.net/10757/676323 |
Nivel de acceso: | acceso embargado |
Materia: | artificial intelligence chatbot depression maturity model software product |
id |
UUPC_5c0c5f1d2266d1170290b164bfa27a80 |
---|---|
oai_identifier_str |
oai:repositorioacademico.upc.edu.pe:10757/676323 |
network_acronym_str |
UUPC |
network_name_str |
UPC-Institucional |
repository_id_str |
2670 |
dc.title.es_PE.fl_str_mv |
Maturity Model Based on a Suitability Approach for the Evaluation of Chatbots Used in Depression Detection |
title |
Maturity Model Based on a Suitability Approach for the Evaluation of Chatbots Used in Depression Detection |
spellingShingle |
Maturity Model Based on a Suitability Approach for the Evaluation of Chatbots Used in Depression Detection David Mori Muñoz, Fernando artificial intelligence chatbot depression maturity model software product |
title_short |
Maturity Model Based on a Suitability Approach for the Evaluation of Chatbots Used in Depression Detection |
title_full |
Maturity Model Based on a Suitability Approach for the Evaluation of Chatbots Used in Depression Detection |
title_fullStr |
Maturity Model Based on a Suitability Approach for the Evaluation of Chatbots Used in Depression Detection |
title_full_unstemmed |
Maturity Model Based on a Suitability Approach for the Evaluation of Chatbots Used in Depression Detection |
title_sort |
Maturity Model Based on a Suitability Approach for the Evaluation of Chatbots Used in Depression Detection |
author |
David Mori Muñoz, Fernando |
author_facet |
David Mori Muñoz, Fernando Alonso Berrocal, Rodrigo David Diaz Amaya, Edgar |
author_role |
author |
author2 |
Alonso Berrocal, Rodrigo David Diaz Amaya, Edgar |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
David Mori Muñoz, Fernando Alonso Berrocal, Rodrigo David Diaz Amaya, Edgar |
dc.subject.es_PE.fl_str_mv |
artificial intelligence chatbot depression maturity model software product |
topic |
artificial intelligence chatbot depression maturity model software product |
description |
In the field of psychology, the use of artificial intelligence-based depression detection chatbots is being employed in order to reduce the percentage of people with depression in the world. However, 3 out of 8 sessions conducted to these software products are not completed due to lack of confidence or self-esteem, trustworthiness and safety of the user. This is due to the disengagement of the chatbot in the conversation it holds with users and the color connotation employed. To avoid producing chatbots with this quality, this research presents a maturity model to evaluate these conversational agents, combining a questionnaire to measure the usability of mobile health applications, a performance metric to measure the chatbot's ability to detect depression, and a proposed category that evaluates whether appropriate depression detection tools were used when training the classification model to detect depression; the results obtained indicate that this model could achieve an average additional accuracy of 6% when evaluating a chatbot. |
publishDate |
2024 |
dc.date.accessioned.none.fl_str_mv |
2024-11-02T05:30:13Z |
dc.date.available.none.fl_str_mv |
2024-11-02T05:30:13Z |
dc.date.issued.fl_str_mv |
2024-01-01 |
dc.type.es_PE.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
dc.identifier.doi.none.fl_str_mv |
10.18687/LACCEI2024.1.1.1547 |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/10757/676323 |
dc.identifier.eissn.none.fl_str_mv |
24146390 |
dc.identifier.journal.es_PE.fl_str_mv |
Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology |
dc.identifier.eid.none.fl_str_mv |
2-s2.0-85203825259 |
dc.identifier.scopusid.none.fl_str_mv |
SCOPUS_ID:85203825259 |
identifier_str_mv |
10.18687/LACCEI2024.1.1.1547 24146390 Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology 2-s2.0-85203825259 SCOPUS_ID:85203825259 |
url |
http://hdl.handle.net/10757/676323 |
dc.language.iso.es_PE.fl_str_mv |
eng |
language |
eng |
dc.rights.es_PE.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.format.es_PE.fl_str_mv |
application/html |
dc.publisher.es_PE.fl_str_mv |
Latin American and Caribbean Consortium of Engineering Institutions |
dc.source.none.fl_str_mv |
reponame:UPC-Institucional instname:Universidad Peruana de Ciencias Aplicadas instacron:UPC |
instname_str |
Universidad Peruana de Ciencias Aplicadas |
instacron_str |
UPC |
institution |
UPC |
reponame_str |
UPC-Institucional |
collection |
UPC-Institucional |
dc.source.journaltitle.none.fl_str_mv |
Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology |
bitstream.url.fl_str_mv |
https://repositorioacademico.upc.edu.pe/bitstream/10757/676323/1/license.txt |
bitstream.checksum.fl_str_mv |
8a4605be74aa9ea9d79846c1fba20a33 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 |
repository.name.fl_str_mv |
Repositorio académico upc |
repository.mail.fl_str_mv |
upc@openrepository.com |
_version_ |
1837187188230455296 |
spelling |
9d31c03f11978bd223cc6165a7ddaf8b300ed885bc5b9cfa712192a511e54624324300c62c2cd43bd6077b81728a19d813eb6dDavid Mori Muñoz, FernandoAlonso Berrocal, RodrigoDavid Diaz Amaya, Edgar2024-11-02T05:30:13Z2024-11-02T05:30:13Z2024-01-0110.18687/LACCEI2024.1.1.1547http://hdl.handle.net/10757/67632324146390Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology2-s2.0-85203825259SCOPUS_ID:85203825259In the field of psychology, the use of artificial intelligence-based depression detection chatbots is being employed in order to reduce the percentage of people with depression in the world. However, 3 out of 8 sessions conducted to these software products are not completed due to lack of confidence or self-esteem, trustworthiness and safety of the user. This is due to the disengagement of the chatbot in the conversation it holds with users and the color connotation employed. To avoid producing chatbots with this quality, this research presents a maturity model to evaluate these conversational agents, combining a questionnaire to measure the usability of mobile health applications, a performance metric to measure the chatbot's ability to detect depression, and a proposed category that evaluates whether appropriate depression detection tools were used when training the classification model to detect depression; the results obtained indicate that this model could achieve an average additional accuracy of 6% when evaluating a chatbot.application/htmlengLatin American and Caribbean Consortium of Engineering Institutionsinfo:eu-repo/semantics/embargoedAccessartificial intelligencechatbotdepressionmaturity modelsoftware productMaturity Model Based on a Suitability Approach for the Evaluation of Chatbots Used in Depression Detectioninfo:eu-repo/semantics/articleProceedings of the LACCEI international Multi-conference for Engineering, Education and Technologyreponame:UPC-Institucionalinstname:Universidad Peruana de Ciencias Aplicadasinstacron:UPCLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorioacademico.upc.edu.pe/bitstream/10757/676323/1/license.txt8a4605be74aa9ea9d79846c1fba20a33MD51false10757/676323oai:repositorioacademico.upc.edu.pe:10757/6763232024-11-02 05:30:14.97Repositorio académico upcupc@openrepository.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 |
score |
13.927358 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).