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HIGEA: An Intelligent Conversational Agent to Detect Caregiver Burden
Mental health disorders increasingly affect people worldwide. As a consequence, more families and relatives find themselves acting as caregivers. Most often, these are untrained people who experience loneliness, abandonment, and often develop signs of depression (i.e., caregiver burden syndrome). In...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9739149/ https://www.ncbi.nlm.nih.gov/pubmed/36498092 http://dx.doi.org/10.3390/ijerph192316019 |
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author | Castilla, Eugenia Escobar, Juan José Villalonga, Claudia Banos, Oresti |
author_facet | Castilla, Eugenia Escobar, Juan José Villalonga, Claudia Banos, Oresti |
author_sort | Castilla, Eugenia |
collection | PubMed |
description | Mental health disorders increasingly affect people worldwide. As a consequence, more families and relatives find themselves acting as caregivers. Most often, these are untrained people who experience loneliness, abandonment, and often develop signs of depression (i.e., caregiver burden syndrome). In this work, we present HIGEA, a digital system based on a conversational agent to help to detect caregiver burden. The conversational agent naturally embeds psychological test questions into informal conversations, which aim at increasing the adherence of use and avoiding user bias. A proof-of-concept is developed based on the popular Zarit Test, which is widely used to assess caregiver burden. Preliminary results show the system is useful and effective. |
format | Online Article Text |
id | pubmed-9739149 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97391492022-12-11 HIGEA: An Intelligent Conversational Agent to Detect Caregiver Burden Castilla, Eugenia Escobar, Juan José Villalonga, Claudia Banos, Oresti Int J Environ Res Public Health Article Mental health disorders increasingly affect people worldwide. As a consequence, more families and relatives find themselves acting as caregivers. Most often, these are untrained people who experience loneliness, abandonment, and often develop signs of depression (i.e., caregiver burden syndrome). In this work, we present HIGEA, a digital system based on a conversational agent to help to detect caregiver burden. The conversational agent naturally embeds psychological test questions into informal conversations, which aim at increasing the adherence of use and avoiding user bias. A proof-of-concept is developed based on the popular Zarit Test, which is widely used to assess caregiver burden. Preliminary results show the system is useful and effective. MDPI 2022-11-30 /pmc/articles/PMC9739149/ /pubmed/36498092 http://dx.doi.org/10.3390/ijerph192316019 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Castilla, Eugenia Escobar, Juan José Villalonga, Claudia Banos, Oresti HIGEA: An Intelligent Conversational Agent to Detect Caregiver Burden |
title | HIGEA: An Intelligent Conversational Agent to Detect Caregiver Burden |
title_full | HIGEA: An Intelligent Conversational Agent to Detect Caregiver Burden |
title_fullStr | HIGEA: An Intelligent Conversational Agent to Detect Caregiver Burden |
title_full_unstemmed | HIGEA: An Intelligent Conversational Agent to Detect Caregiver Burden |
title_short | HIGEA: An Intelligent Conversational Agent to Detect Caregiver Burden |
title_sort | higea: an intelligent conversational agent to detect caregiver burden |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9739149/ https://www.ncbi.nlm.nih.gov/pubmed/36498092 http://dx.doi.org/10.3390/ijerph192316019 |
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