A Neutrosophic Cognitive Map-Based Modeling Framework for Analyzing the Indeterminate Impact of Exercise on University Students’ Mental Health

Abstract

The relationship between physical exercise and mental health in university 
students is characterized by complexity, ambiguity, and contextual variability. 
Traditional modeling approaches often fail to capture the indeterminate, uncertain, and 
contradictory nature of these interactions. In this study, we introduce a novel analytical 
framework based on Neutrosophic Cognitive Maps (NCMs) to model and examine the 
multidimensional effects of exercise interventions on the mental health of university 
students. NCMs extend Fuzzy Cognitive Maps by integrating the concept of 
indeterminacy, allowing experts to express not only positive or negative causal 
relationships but also undefined or inconclusive ones. This approach is particularly 
suitable for modeling psychosocial systems, where subjective interpretation and 
ambiguity are common.We construct an NCM with ten interrelated concepts ranging 
from exercise intensity, sleep quality, and academic stress to anxiety levels and social 
support and encode the causal influences among them using neutrosophic logic. Through 
iterative simulations and matrix-based transformations, we analyze the dynamic behavior 
of the system, identify equilibrium states (fixed points), and explore the emergence of 
limit cycles. The results reveal nuanced interaction patterns that highlight the moderating 
and mediating roles of indeterminate factors, such as emotional volatility and 
environmental context, in shaping mental health outcomes. This paper provides a 
mathematically rigorous yet intuitively interpretable tool for researchers and practitioners 
in health sciences and psychology. It opens new pathways for the design of adaptive, 
personalized mental health interventions grounded in systems thinking and neutrosophic 
logic.

DOI: 10.5281/zenodo.15540409