Malaysian Journal of Mathematical Sciences, March 2026, Vol. 20, No. 1
Application of Exploratory and Confirmatory Factor Analysis to Model Loneliness Dimensions Among Pre-University Students
Juhan, N., Hoque, M. Z.,Isha, D. S. N. S. A, Zubairi, Y. Z., and Al Mamun, A. S. M.
Corresponding Email: liyana87@ums.edu.my
Received date: 13 April 2025
Accepted date: 28 July 2025
Abstract:
As students transition from secondary to higher education, they often face emotional and social challenges that influence their sense of connection and psychological well-being. This study applies factor analysis techniques to examine the multidimensional nature of loneliness among pre-university students. Data were collected from 219 Foundation Program students using the University of California, Los Angeles (UCLA) Loneliness Scale. The Kaiser--Meyer--Olkin (KMO) test and Bartlett's test of sphericity were conducted to assess the data's suitability for factor analysis. The KMO value exceeded 0.6 and Bartlett's test was significant, indicating the data was appropriate for further analysis. Exploratory Factor Analysis (EFA) was conducted to identify the fundamental structure of the scale, while Confirmatory Factor Analysis (CFA) validated the results. Cronbach's alpha was calculated to assess reliability. The findings of EFA and CFA align with previous empirical studies, confirming three distinct dimensions of loneliness: isolation, relational connectedness, and collective connectedness. The derived factors showed satisfactory reliability, with scores exceeding 0.8. This study demonstrates the applicability of factor analysis in modeling multidimensional psychological constructs. The results support the structure of the UCLA Loneliness Scale and offer insights into future research and data-informed interventions to enhance student well-being.
Keywords: loneliness; pre-university students; UCLA Loneliness Scale; exploratory factor analysis (EFA); confirmatory factor analysis (CFA).
