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Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques
BACKGROUND: Adverse Childhood Experiences (ACEs), a set of negative events and processes that a person might encounter during childhood and adolescence, have been proven to be linked to increased risks of a multitude of negative health outcomes and conditions when children reach adulthood and beyond...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6707574/ https://www.ncbi.nlm.nih.gov/pubmed/31115344 http://dx.doi.org/10.2196/13498 |
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author | Brenas, Jon Hael Shin, Eun Kyong Shaban-Nejad, Arash |
author_facet | Brenas, Jon Hael Shin, Eun Kyong Shaban-Nejad, Arash |
author_sort | Brenas, Jon Hael |
collection | PubMed |
description | BACKGROUND: Adverse Childhood Experiences (ACEs), a set of negative events and processes that a person might encounter during childhood and adolescence, have been proven to be linked to increased risks of a multitude of negative health outcomes and conditions when children reach adulthood and beyond. OBJECTIVE: To better understand the relationship between ACEs and their relevant risk factors with associated health outcomes and to eventually design and implement preventive interventions, access to an integrated coherent dataset is needed. Therefore, we implemented a formal ontology as a resource to allow the mental health community to facilitate data integration and knowledge modeling and to improve ACEs’ surveillance and research. METHODS: We use advanced knowledge representation and semantic Web tools and techniques to implement the ontology. The current implementation of the ontology is expressed in the description logic ALCRIQ(D), a sublogic of Web Ontology Language (OWL 2). RESULTS: The ACEs Ontology has been implemented and made available to the mental health community and the public via the BioPortal repository. Moreover, multiple use-case scenarios have been introduced to showcase and evaluate the usability of the ontology in action. The ontology was created to be used by major actors in the ACEs community with different applications, from the diagnosis of individuals and predicting potential negative outcomes that they might encounter to the prevention of ACEs in a population and designing interventions and policies. CONCLUSIONS: The ACEs Ontology provides a uniform and reusable semantic network and an integrated knowledge structure for mental health practitioners and researchers to improve ACEs’ surveillance and evaluation. |
format | Online Article Text |
id | pubmed-6707574 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-67075742019-11-18 Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques Brenas, Jon Hael Shin, Eun Kyong Shaban-Nejad, Arash JMIR Ment Health Original Paper BACKGROUND: Adverse Childhood Experiences (ACEs), a set of negative events and processes that a person might encounter during childhood and adolescence, have been proven to be linked to increased risks of a multitude of negative health outcomes and conditions when children reach adulthood and beyond. OBJECTIVE: To better understand the relationship between ACEs and their relevant risk factors with associated health outcomes and to eventually design and implement preventive interventions, access to an integrated coherent dataset is needed. Therefore, we implemented a formal ontology as a resource to allow the mental health community to facilitate data integration and knowledge modeling and to improve ACEs’ surveillance and research. METHODS: We use advanced knowledge representation and semantic Web tools and techniques to implement the ontology. The current implementation of the ontology is expressed in the description logic ALCRIQ(D), a sublogic of Web Ontology Language (OWL 2). RESULTS: The ACEs Ontology has been implemented and made available to the mental health community and the public via the BioPortal repository. Moreover, multiple use-case scenarios have been introduced to showcase and evaluate the usability of the ontology in action. The ontology was created to be used by major actors in the ACEs community with different applications, from the diagnosis of individuals and predicting potential negative outcomes that they might encounter to the prevention of ACEs in a population and designing interventions and policies. CONCLUSIONS: The ACEs Ontology provides a uniform and reusable semantic network and an integrated knowledge structure for mental health practitioners and researchers to improve ACEs’ surveillance and evaluation. JMIR Publications 2019-05-21 /pmc/articles/PMC6707574/ /pubmed/31115344 http://dx.doi.org/10.2196/13498 Text en ©Jon Hael Brenas, Eun Kyong Shin, Arash Shaban-Nejad. Originally published in JMIR Mental Health (http://mental.jmir.org), 21.05.2019. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on http://mental.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Brenas, Jon Hael Shin, Eun Kyong Shaban-Nejad, Arash Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques |
title | Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques |
title_full | Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques |
title_fullStr | Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques |
title_full_unstemmed | Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques |
title_short | Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques |
title_sort | adverse childhood experiences ontology for mental health surveillance, research, and evaluation: advanced knowledge representation and semantic web techniques |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6707574/ https://www.ncbi.nlm.nih.gov/pubmed/31115344 http://dx.doi.org/10.2196/13498 |
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