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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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Behavioural Neurology |
| Online Access: | http://dx.doi.org/10.1155/2023/8552180 |
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| author | Nidal Moukaddam Bishal Lamichhane Ramiro Salas Wayne Goodman Ashutosh Sabharwal |
| author_facet | Nidal Moukaddam Bishal Lamichhane Ramiro Salas Wayne Goodman Ashutosh Sabharwal |
| author_sort | Nidal Moukaddam |
| collection | DOAJ |
| 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 | Article |
| id | doaj-art-7d688c40a4f04a04af21be6cee150f69 |
| institution | DOAJ |
| issn | 1875-8584 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Behavioural Neurology |
| spelling | doaj-art-7d688c40a4f04a04af21be6cee150f692025-08-20T03:07:04ZengWileyBehavioural Neurology1875-85842023-01-01202310.1155/2023/8552180Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health DisorderNidal Moukaddam0Bishal Lamichhane1Ramiro Salas2Wayne Goodman3Ashutosh Sabharwal4Menninger Department of PsychiatryElectrical and Computer EngineeringMenninger Department of PsychiatryMenninger Department of PsychiatryElectrical and Computer EngineeringIntroduction. 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.http://dx.doi.org/10.1155/2023/8552180 |
| spellingShingle | Nidal Moukaddam Bishal Lamichhane Ramiro Salas Wayne Goodman Ashutosh Sabharwal Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder Behavioural Neurology |
| 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 |
| url | http://dx.doi.org/10.1155/2023/8552180 |
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