Cargando…
A network analysis approach to ADHD symptoms: More than the sum of its parts
In interpreting attention-deficit/hyperactivity disorder (ADHD) symptoms, categorical and dimensional approaches are commonly used. Both employ binary symptom counts which give equal weighting, with little attention to the combinations and relative contributions of individual symptoms. Alternatively...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6338383/ https://www.ncbi.nlm.nih.gov/pubmed/30657783 http://dx.doi.org/10.1371/journal.pone.0211053 |
_version_ | 1783388444117958656 |
---|---|
author | Silk, Timothy J. Malpas, Charles B. Beare, Richard Efron, Daryl Anderson, Vicki Hazell, Philip Jongeling, Brad Nicholson, Jan M. Sciberras, Emma |
author_facet | Silk, Timothy J. Malpas, Charles B. Beare, Richard Efron, Daryl Anderson, Vicki Hazell, Philip Jongeling, Brad Nicholson, Jan M. Sciberras, Emma |
author_sort | Silk, Timothy J. |
collection | PubMed |
description | In interpreting attention-deficit/hyperactivity disorder (ADHD) symptoms, categorical and dimensional approaches are commonly used. Both employ binary symptom counts which give equal weighting, with little attention to the combinations and relative contributions of individual symptoms. Alternatively, symptoms can be viewed as an interacting network, revealing the complex relationship between symptoms. Using a novel network modelling approach, this study explores the relationships between the 18 symptoms in the Diagnostic Statistical Manual (DSM-5) criteria and whether network measures are useful in predicting outcomes. Participants were from a community cohort, the Children’s Attention Project. DSM ADHD symptoms were recorded in a face-to-face structured parent interview for 146 medication naïve children with ADHD and 209 controls (aged 6–8 years). Analyses indicated that not all symptoms are equal. Frequencies of endorsement and configurations of symptoms varied, with certain symptoms playing a more important role within the ADHD symptom network. In total, 116,220 combinations of symptoms within a diagnosis of ADHD were identified, with 92% demonstrating a unique symptom configuration. Symptom association networks highlighted the relative importance of hyperactive/impulsive symptoms in the symptom network. In particular, the ‘motoric’-type symptoms as well as interrupts as a marker of impulsivity in the hyperactive domain, as well as loses things and does not follow instructions in the inattentive domain, had high measures of centrality. Centrality-measure weighted symptom counts showed significant association with clinical but not cognitive outcomes, however the relationships were not significantly stronger than symptom count alone. The finding may help to explain heterogeneity in the ADHD phenotype. |
format | Online Article Text |
id | pubmed-6338383 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-63383832019-01-30 A network analysis approach to ADHD symptoms: More than the sum of its parts Silk, Timothy J. Malpas, Charles B. Beare, Richard Efron, Daryl Anderson, Vicki Hazell, Philip Jongeling, Brad Nicholson, Jan M. Sciberras, Emma PLoS One Research Article In interpreting attention-deficit/hyperactivity disorder (ADHD) symptoms, categorical and dimensional approaches are commonly used. Both employ binary symptom counts which give equal weighting, with little attention to the combinations and relative contributions of individual symptoms. Alternatively, symptoms can be viewed as an interacting network, revealing the complex relationship between symptoms. Using a novel network modelling approach, this study explores the relationships between the 18 symptoms in the Diagnostic Statistical Manual (DSM-5) criteria and whether network measures are useful in predicting outcomes. Participants were from a community cohort, the Children’s Attention Project. DSM ADHD symptoms were recorded in a face-to-face structured parent interview for 146 medication naïve children with ADHD and 209 controls (aged 6–8 years). Analyses indicated that not all symptoms are equal. Frequencies of endorsement and configurations of symptoms varied, with certain symptoms playing a more important role within the ADHD symptom network. In total, 116,220 combinations of symptoms within a diagnosis of ADHD were identified, with 92% demonstrating a unique symptom configuration. Symptom association networks highlighted the relative importance of hyperactive/impulsive symptoms in the symptom network. In particular, the ‘motoric’-type symptoms as well as interrupts as a marker of impulsivity in the hyperactive domain, as well as loses things and does not follow instructions in the inattentive domain, had high measures of centrality. Centrality-measure weighted symptom counts showed significant association with clinical but not cognitive outcomes, however the relationships were not significantly stronger than symptom count alone. The finding may help to explain heterogeneity in the ADHD phenotype. Public Library of Science 2019-01-18 /pmc/articles/PMC6338383/ /pubmed/30657783 http://dx.doi.org/10.1371/journal.pone.0211053 Text en © 2019 Silk et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Silk, Timothy J. Malpas, Charles B. Beare, Richard Efron, Daryl Anderson, Vicki Hazell, Philip Jongeling, Brad Nicholson, Jan M. Sciberras, Emma A network analysis approach to ADHD symptoms: More than the sum of its parts |
title | A network analysis approach to ADHD symptoms: More than the sum of its parts |
title_full | A network analysis approach to ADHD symptoms: More than the sum of its parts |
title_fullStr | A network analysis approach to ADHD symptoms: More than the sum of its parts |
title_full_unstemmed | A network analysis approach to ADHD symptoms: More than the sum of its parts |
title_short | A network analysis approach to ADHD symptoms: More than the sum of its parts |
title_sort | network analysis approach to adhd symptoms: more than the sum of its parts |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6338383/ https://www.ncbi.nlm.nih.gov/pubmed/30657783 http://dx.doi.org/10.1371/journal.pone.0211053 |
work_keys_str_mv | AT silktimothyj anetworkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT malpascharlesb anetworkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT bearerichard anetworkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT efrondaryl anetworkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT andersonvicki anetworkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT hazellphilip anetworkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT jongelingbrad anetworkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT nicholsonjanm anetworkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT sciberrasemma anetworkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT silktimothyj networkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT malpascharlesb networkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT bearerichard networkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT efrondaryl networkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT andersonvicki networkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT hazellphilip networkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT jongelingbrad networkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT nicholsonjanm networkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts AT sciberrasemma networkanalysisapproachtoadhdsymptomsmorethanthesumofitsparts |