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Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder
INTRODUCTION: Suicide is one of the leading causes of death across different age groups. The persistence of suicidal ideation and the progression of suicidal ideations to action could be related to impulsivity, the tendency to act on urges with low temporal latency, and little forethought. Quantifyi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423091/ https://www.ncbi.nlm.nih.gov/pubmed/37575401 http://dx.doi.org/10.1155/2023/8552180 |
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author | Moukaddam, Nidal Lamichhane, Bishal Salas, Ramiro Goodman, Wayne Sabharwal, Ashutosh |
author_facet | Moukaddam, Nidal Lamichhane, Bishal Salas, Ramiro Goodman, Wayne Sabharwal, Ashutosh |
author_sort | Moukaddam, Nidal |
collection | PubMed |
description | INTRODUCTION: Suicide is one of the leading causes of death across different age groups. The persistence of suicidal ideation and the progression of suicidal ideations to action could be related to impulsivity, the tendency to act on urges with low temporal latency, and little forethought. Quantifying impulsivity could thus help suicidality estimation and risk assessments in ideation-to-action suicidality frameworks. METHODS: To model suicidality with impulsivity quantification, we obtained questionnaires, behavioral tests, heart rate variability (HRV), and resting state functional magnetic resonance imaging measurements from 34 participants with mood disorders. The participants were categorized into three suicidality groups based on their Mini-International Neuropsychiatric Interview: none, low, and moderate to severe. RESULTS: Questionnaire and HRV-based impulsivity measures were significantly different between the suicidality groups with higher subscales of impulsivity associated with higher suicidality. A multimodal system to characterize impulsivity objectively resulted in a classification accuracy of 96.77% in the three-class suicidality group prediction task. CONCLUSIONS: This study elucidates the relative sensitivity of various impulsivity measures in differentiating participants with suicidality and demonstrates suicidality prediction with high accuracy using a multimodal objective impulsivity characterization in participants with mood disorders. |
format | Online Article Text |
id | pubmed-10423091 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-104230912023-08-13 Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder Moukaddam, Nidal Lamichhane, Bishal Salas, Ramiro Goodman, Wayne Sabharwal, Ashutosh Behav Neurol Research Article INTRODUCTION: Suicide is one of the leading causes of death across different age groups. The persistence of suicidal ideation and the progression of suicidal ideations to action could be related to impulsivity, the tendency to act on urges with low temporal latency, and little forethought. Quantifying impulsivity could thus help suicidality estimation and risk assessments in ideation-to-action suicidality frameworks. METHODS: To model suicidality with impulsivity quantification, we obtained questionnaires, behavioral tests, heart rate variability (HRV), and resting state functional magnetic resonance imaging measurements from 34 participants with mood disorders. The participants were categorized into three suicidality groups based on their Mini-International Neuropsychiatric Interview: none, low, and moderate to severe. RESULTS: Questionnaire and HRV-based impulsivity measures were significantly different between the suicidality groups with higher subscales of impulsivity associated with higher suicidality. A multimodal system to characterize impulsivity objectively resulted in a classification accuracy of 96.77% in the three-class suicidality group prediction task. CONCLUSIONS: This study elucidates the relative sensitivity of various impulsivity measures in differentiating participants with suicidality and demonstrates suicidality prediction with high accuracy using a multimodal objective impulsivity characterization in participants with mood disorders. Hindawi 2023-08-05 /pmc/articles/PMC10423091/ /pubmed/37575401 http://dx.doi.org/10.1155/2023/8552180 Text en Copyright © 2023 Nidal Moukaddam et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Moukaddam, Nidal Lamichhane, Bishal Salas, Ramiro Goodman, Wayne Sabharwal, Ashutosh Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder |
title | Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder |
title_full | Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder |
title_fullStr | Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder |
title_full_unstemmed | Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder |
title_short | Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder |
title_sort | modeling suicidality with multimodal impulsivity characterization in participants with mental health disorder |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423091/ https://www.ncbi.nlm.nih.gov/pubmed/37575401 http://dx.doi.org/10.1155/2023/8552180 |
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