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Identification of nonclinical interventions for spontaneous recovery of depression using mathematical modeling

BACKGROUND: In order to make a risk or vulnerability assessment of major depressive disorder (MDD) in adolescents and suggest nonclinical interventions for spontaneous recovery for low‐vulnerable adolescents a novel network mathematical model has been proposed. METHODS: In the existing network theor...

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Autores principales: Mohan, Gayathree, Kandaswamy, Dinesh Kumar, Chikkaharohalli Ramakrishna, Mohan Kumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7066340/
https://www.ncbi.nlm.nih.gov/pubmed/32026616
http://dx.doi.org/10.1002/brb3.1550
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author Mohan, Gayathree
Kandaswamy, Dinesh Kumar
Chikkaharohalli Ramakrishna, Mohan Kumar
author_facet Mohan, Gayathree
Kandaswamy, Dinesh Kumar
Chikkaharohalli Ramakrishna, Mohan Kumar
author_sort Mohan, Gayathree
collection PubMed
description BACKGROUND: In order to make a risk or vulnerability assessment of major depressive disorder (MDD) in adolescents and suggest nonclinical interventions for spontaneous recovery for low‐vulnerable adolescents a novel network mathematical model has been proposed. METHODS: In the existing network theory, the theoretical model consists of a symptom network surrounded by the triggering factors as external field which are the cause for adolescents being diagnosed with MDD. But in our network model, the triggering external field is replaced by nonclinical interventions, easily implementable in schools and colleges with teachers as facilitators. RESULTS: The four variables of subjective well‐being (SWB), emotional quotient—Attention (EQ‐A), emotional quotient—Clarity (EQ‐C) and emotional quotient—Reparation (EQ‐R) were the symptoms considered for stratification of the vulnerability. The mathematical model was created using the four symptoms and the four nonclinical interventions of technology use, physical exercise, peer pressure positive and peer pressure negative, and their inter‐relationship. CONCLUSION: A balance of tech use and physical exercise and of the peer pressure help maintain the adolescents in the low‐vulnerability group in our study with 227 adolescents in Bangalore. Furthermore, we predict that positive peer pressure and physical exercise could increase the EQ thus suggesting a preventive model for the onset of major depressive disorder (MDD).
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spelling pubmed-70663402020-03-18 Identification of nonclinical interventions for spontaneous recovery of depression using mathematical modeling Mohan, Gayathree Kandaswamy, Dinesh Kumar Chikkaharohalli Ramakrishna, Mohan Kumar Brain Behav Original Research BACKGROUND: In order to make a risk or vulnerability assessment of major depressive disorder (MDD) in adolescents and suggest nonclinical interventions for spontaneous recovery for low‐vulnerable adolescents a novel network mathematical model has been proposed. METHODS: In the existing network theory, the theoretical model consists of a symptom network surrounded by the triggering factors as external field which are the cause for adolescents being diagnosed with MDD. But in our network model, the triggering external field is replaced by nonclinical interventions, easily implementable in schools and colleges with teachers as facilitators. RESULTS: The four variables of subjective well‐being (SWB), emotional quotient—Attention (EQ‐A), emotional quotient—Clarity (EQ‐C) and emotional quotient—Reparation (EQ‐R) were the symptoms considered for stratification of the vulnerability. The mathematical model was created using the four symptoms and the four nonclinical interventions of technology use, physical exercise, peer pressure positive and peer pressure negative, and their inter‐relationship. CONCLUSION: A balance of tech use and physical exercise and of the peer pressure help maintain the adolescents in the low‐vulnerability group in our study with 227 adolescents in Bangalore. Furthermore, we predict that positive peer pressure and physical exercise could increase the EQ thus suggesting a preventive model for the onset of major depressive disorder (MDD). John Wiley and Sons Inc. 2020-02-05 /pmc/articles/PMC7066340/ /pubmed/32026616 http://dx.doi.org/10.1002/brb3.1550 Text en © 2020 The Authors. Brain and Behavior published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Mohan, Gayathree
Kandaswamy, Dinesh Kumar
Chikkaharohalli Ramakrishna, Mohan Kumar
Identification of nonclinical interventions for spontaneous recovery of depression using mathematical modeling
title Identification of nonclinical interventions for spontaneous recovery of depression using mathematical modeling
title_full Identification of nonclinical interventions for spontaneous recovery of depression using mathematical modeling
title_fullStr Identification of nonclinical interventions for spontaneous recovery of depression using mathematical modeling
title_full_unstemmed Identification of nonclinical interventions for spontaneous recovery of depression using mathematical modeling
title_short Identification of nonclinical interventions for spontaneous recovery of depression using mathematical modeling
title_sort identification of nonclinical interventions for spontaneous recovery of depression using mathematical modeling
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7066340/
https://www.ncbi.nlm.nih.gov/pubmed/32026616
http://dx.doi.org/10.1002/brb3.1550
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