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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...

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Autores principales: Moukaddam, Nidal, Lamichhane, Bishal, Salas, Ramiro, Goodman, Wayne, Sabharwal, Ashutosh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2023
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.
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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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