Multilevel Latent Profile Analysis: Identifying Students' Mental Health and Well-Being Typologies

• In Event: Assessing and Designing Self-Regulation of Learning Interventions

Abstract

The present study aims at investigating students’ mental health and wellbeing (MHWB) profiles using a
multilevel latent profile analysis (MPLA) approach. The data used in this study are from 229 university
students measured ten times over the course of an academic semester. MLPA models were employed to
take into account the nested structure of the data (i.e., individuals nested within measurement occasions).
Results identified predominant intra-individual and inter-individual patterns of variation in students’
MHWB as well as the extent to which self-reported behavioral engagement, academic performance and
sex are associated with the probability of being characterized as a particular latent profile.

Authors

• Ramin Rostampour, University of Victoria

• Sarah K Davis, University of Victoria

• Allyson F. Hadwin, University of Victoria