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

利用数学模型识别促进抑郁症自发康复的非临床干预措施

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Abstract

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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