Latent Profile Analysis of Mental Health among Chinese University Students: Evidence for the Dual-Factor Model.

Abstract

The dual-factor model of mental health has garnered substantial support, positing the necessity of encompassing both negative (e.g., psychological problems) and positive (e.g., well-being) indicators in comprehensive evaluations of people's mental health. Nonetheless, the nature of the profiles and predictors (such as academic emotions) during four years of university life lack clarity, hampering a profound understanding of mental well-being among university students. This research included 135 items designed to assess an array of depression symptoms, negative emotional experiences, life satisfaction, positive emotional experiences, and academic emotions. First, this research affirmed the applicability of the dual-factor model in the context of Chinese university students (N = 2277) with the utilization of confirmatory factor analysis (CFA). Furthermore, latent profile analysis (LPA) was employed to delineate prevalent constellations of psychological symptoms and subjective well-being within participants. The outcomes unveiled the existence of three distinct clusters: (1) Complete Mental Health, (2) Vulnerable, and (3) Troubled. Third, by employing R3stept on academic emotions and mental health classifications, this study revealed that there were associations between this variable and specific amalgams of psychological symptoms and well-being levels. These findings bear influence on the practice of mental health screening and the identification of individuals necessitating targeted interventions.