Profiling Depression Risk and Psychological Well-Being in Elderly: A Fuzzy Multicriteria Approach

Abstract

The purpose of this study is to analyze depression and psychological well-being in older adults in the city of Bello, Colombia, by identifying clusters of individuals with varying levels of risk to explore the implications for care and support. To achieve this objective, 164 older adults were surveyed using the GDS-15 Scale to measure depression. Cluster analysis was employed to classify groups with similar depression risk profiles and psychological well-being. Additionally, Cronbach's alpha was used to determine the reliability of latent constructs. A Fuzzy Hierarchical Process Analysis model, supplemented by expert input and surveys, was utilized to prioritize risk levels and rank sub-factors by their local and global weight in the model.

The study identifies three critical clusters that influence the level of depression risk in the population: Emotional State and Life Satisfaction (46.78%), Cognitive Ability and Self-Esteem (35.87%), and Social Interaction and Activities (17.35%). These findings underscore the importance of considering a variety of interrelated factors, highlighting that emotional health, cognitive self-esteem, and social interactions are essential determinants in the assessment of depression risk.

This multidimensional approach is crucial for the development of more effective preventive and therapeutic strategies in the fight against depression. The results suggest that a significant proportion of older adults are at high risk for depression, emphasizing the need for comprehensive and tailored interventions to address their unique needs.