Mathematical Modeling and Dynamical Analysis of Job Anxiety in a Student Population
Abstract
This study proposes a comprehensive mathematical framework to investigate the emergence, progression, and reduction of job anxiety among senior undergraduate students and recent graduates. Job anxiety has emerged as a prominent psychological concern for students, stemming from a multitude of factors, including uncertainty regarding future employment prospects, academic pressure, and the transition to professional life. To capture the dynamic nature of this phenomenon, a compartment-based model is constructed by categorizing individuals into groups representing different levels of susceptibility, risk, anxiety, support, and recovery. The model diagram and the associated system of differential equations are formulated to describe the transitions between these parameters. The equilibrium points of the system are identified, and their stability properties are analyzed to determine the conditions under which job anxiety persists or diminishes within the population. The numerical analyses are conducted using parameter values obtained through a survey administered to university students. The simulation results demonstrate the progression of job anxiety over time and underscore the factors that contribute to its escalation or mitigation. These findings offer a quantitative perspective on the psychological challenges faced by students and demonstrate the potential of dynamic modeling to inform support strategies and intervention policies. The study concludes by focusing on the theoretical and practical implications of the proposed model and delineating future research directions to enhance student well-being during the transition to professional life.
Keywords
References
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Details
Primary Language
English
Subjects
Numerical Solution of Differential and Integral Equations, Numerical Analysis, Dynamical Systems in Applications
Journal Section
Research Article
Authors
Publication Date
March 30, 2026
Submission Date
December 11, 2025
Acceptance Date
March 5, 2026
Published in Issue
Year 2026 Number: 54