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Mathematical modelling, analysis and numerical simulation of social media addiction and depression.
Ali, Abu Safyan; Javeed, Shumaila; Faiz, Zeshan; Baleanu, Dumitru.
Afiliação
  • Ali AS; Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy.
  • Javeed S; Department of Mathematics, COMSATS University Islamabad, Islamabad Campus, Islamabad, Pakistan.
  • Faiz Z; Department of Mathematics, COMSATS University Islamabad, Islamabad Campus, Islamabad, Pakistan.
  • Baleanu D; Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon.
PLoS One ; 19(3): e0293807, 2024.
Article em En | MEDLINE | ID: mdl-38470872
ABSTRACT
We formulate a mathematical model of social media addiction and depression (SMAD) in this study. Key aspects, such as social media addiction and depression disease-free equilibrium point (SMADDFEP), social media addiction and depression endemic equilibrium point (SMADEEP), and basic reproduction number (R0), have been analyzed qualitatively. The results indicate that if R0 < 1, the SMADDFEP is locally asymptotically stable. The global asymptotic stability of the SMADDFEP has been established using the Castillo-Chavez theorem. On the other hand, if R0 > 1, the unique endemic equilibrium point (SMADEEP) is locally asymptotically stable by Lyapunov theorem, and the model exhibits a forward bifurcation at R0 = 1 according to the Center Manifold theorem. To examine the model's sensitivity, we calculated the normalized forward sensitivity index and conducted a Partial Rank Correlation Coefficient (PRCC) analysis to describe the influence of parameters on the SMAD. The numerical results obtained using the Fourth-order Runge-Kutta (RK-4) scheme show that increasing the number of addicted individuals leads to an increase in the number of depressed individuals.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Depressão / Transtorno de Adição à Internet Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Depressão / Transtorno de Adição à Internet Idioma: En Ano de publicação: 2024 Tipo de documento: Article