A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHD
BackgroundAttention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder in children and adolescents characterized by persistent patterns of hyperactivity, impulsivity, and inattentiveness. ADHD persists for many into adulthood. While irritability is not a diagnostic symptom...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1467486/full |
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| author | Saeedeh Komijani Dipak Ghosal Manpreet K. Singh Julie B. Schweitzer Julie B. Schweitzer Prerona Mukherjee Prerona Mukherjee |
| author_facet | Saeedeh Komijani Dipak Ghosal Manpreet K. Singh Julie B. Schweitzer Julie B. Schweitzer Prerona Mukherjee Prerona Mukherjee |
| author_sort | Saeedeh Komijani |
| collection | DOAJ |
| description | BackgroundAttention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder in children and adolescents characterized by persistent patterns of hyperactivity, impulsivity, and inattentiveness. ADHD persists for many into adulthood. While irritability is not a diagnostic symptom of ADHD, temper outbursts and irritable moods are common in individuals with ADHD. However, research on the association between irritability and ADHD symptoms in adolescents and young adults remains limited.MethodPrior research has used linear regression models to examine longitudinal relations between ADHD and irritability symptoms. This method may be impacted by the potential presence of highly colinear variables. We utilized a hierarchical clustering technique to mitigate these collinearity issues and implemented a non-parametric machine learning (ML) model to predict the significance of symptom relations over time. Our data included adolescents (N=148, 54% ADHD) and young adults (N=124, 42% ADHD) diagnosed with ADHD and neurotypical (NT) individuals, evaluated in a longitudinal study.ResultsResults from the linear regression analysis indicate a significant association between irritability at time-point 1 (T1) and hyperactive-impulsive symptoms at time-point 2 (T2) in adolescent females (β=0.26, p-value < 0.001), and inattentiveness at T1 with irritability at T2 in young adult females (β=0.49, p-value < 0.05). Using a non-parametric-based approach, employing the Random Forest (RF) method, we found that among both adolescents and young adults, irritability in adolescent females significantly contributes to predicting impulsive symptoms in subsequent years, achieving a performance rate of 86%.ConclusionOur results corroborate and extend prior findings, allowing for an in-depth examination of longitudinal relations between irritability and ADHD symptoms, namely hyperactivity, impulsivity, and inattentiveness, and the unique association between irritability and ADHD symptoms in females. |
| format | Article |
| id | doaj-art-d8e5d1fba68f442b9ff8ca45434db208 |
| institution | Kabale University |
| issn | 1664-0640 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj-art-d8e5d1fba68f442b9ff8ca45434db2082025-02-12T07:26:28ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402025-02-011510.3389/fpsyt.2024.14674861467486A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHDSaeedeh Komijani0Dipak Ghosal1Manpreet K. Singh2Julie B. Schweitzer3Julie B. Schweitzer4Prerona Mukherjee5Prerona Mukherjee6Department of Computer Science, University of California, Davis, Davis, CA, United StatesDepartment of Computer Science, University of California, Davis, Davis, CA, United StatesDepartment of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA, United StatesDepartment of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA, United StatesMIND Institute, University of California, Davis, Davis, CA, United StatesDepartment of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA, United StatesMIND Institute, University of California, Davis, Davis, CA, United StatesBackgroundAttention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder in children and adolescents characterized by persistent patterns of hyperactivity, impulsivity, and inattentiveness. ADHD persists for many into adulthood. While irritability is not a diagnostic symptom of ADHD, temper outbursts and irritable moods are common in individuals with ADHD. However, research on the association between irritability and ADHD symptoms in adolescents and young adults remains limited.MethodPrior research has used linear regression models to examine longitudinal relations between ADHD and irritability symptoms. This method may be impacted by the potential presence of highly colinear variables. We utilized a hierarchical clustering technique to mitigate these collinearity issues and implemented a non-parametric machine learning (ML) model to predict the significance of symptom relations over time. Our data included adolescents (N=148, 54% ADHD) and young adults (N=124, 42% ADHD) diagnosed with ADHD and neurotypical (NT) individuals, evaluated in a longitudinal study.ResultsResults from the linear regression analysis indicate a significant association between irritability at time-point 1 (T1) and hyperactive-impulsive symptoms at time-point 2 (T2) in adolescent females (β=0.26, p-value < 0.001), and inattentiveness at T1 with irritability at T2 in young adult females (β=0.49, p-value < 0.05). Using a non-parametric-based approach, employing the Random Forest (RF) method, we found that among both adolescents and young adults, irritability in adolescent females significantly contributes to predicting impulsive symptoms in subsequent years, achieving a performance rate of 86%.ConclusionOur results corroborate and extend prior findings, allowing for an in-depth examination of longitudinal relations between irritability and ADHD symptoms, namely hyperactivity, impulsivity, and inattentiveness, and the unique association between irritability and ADHD symptoms in females.https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1467486/fullADHDirritabilityadolescentsyoung adultssymptom predictionhierarchical clustering |
| spellingShingle | Saeedeh Komijani Dipak Ghosal Manpreet K. Singh Julie B. Schweitzer Julie B. Schweitzer Prerona Mukherjee Prerona Mukherjee A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHD Frontiers in Psychiatry ADHD irritability adolescents young adults symptom prediction hierarchical clustering |
| title | A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHD |
| title_full | A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHD |
| title_fullStr | A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHD |
| title_full_unstemmed | A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHD |
| title_short | A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHD |
| title_sort | novel framework to predict adhd symptoms using irritability in adolescents and young adults with and without adhd |
| topic | ADHD irritability adolescents young adults symptom prediction hierarchical clustering |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1467486/full |
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