Application of latent class modelling in students� life skills: The case of Iran university of medical sciences

Abstract

Background: Many people facing life difficulties are unable to sort out these problems. Objectives: A study was designed to determine students� life skills at the Iran University of Medical Sciences (IUMS). Methods: This cross-sectional study was conducted at IUMS in 2016-17 with a sample of 342 students. A questionnaire was used with multi-choice questions from poor to high skills. Latent class models were applied for data analysis using Mplus. Bayesian information criterion (BIC) and Bootstrap likelihood ratio tests were used to determine the number of classes. Results: A two-class model had the best fit since the BIC had the lowest amount. Almost 76 and 24 of the cases entered the high and moderate skill classes of the model, respectively. The level of education (LOE) was the only significant variable (P = 0.004) for classifying the students. Conclusions: The model could predict the probability of high life skilled students. Also, LOE had a high impact on the probability of high life skills. © 2020, Author(s)