Abstract
Background: It is well known that the university period is an important stage for young adults, involving significant academic and psychosocial adjustments. Students with greater Mental Health Literacy (MHL), which is defined as the knowledge, beliefs, and skills individuals have regarding mental health and mental illness, are better able to identify difficulties, seek help, and adopt healthier coping strategies. This study aims to describe the MHL levels of undergraduate health students and identify associated factors related to academic life, mental health and psychological state. Methods: A cross-sectional, self-administered, web-based survey was conducted using a non-probability sampling strategy among undergraduate students in health-related degrees at a Portuguese higher-education institution. Data was collected using a general characterization questionnaire and the following instruments: MHL Questionnaire, Academic Life Satisfaction, Subjective Happiness Scale, Psychological Well-Being Scale (PWBS), and Depression Anxiety Stress Scale. Bivariate and linear regression analyses were employed to identify factors associated with MHL. Results: A total of 306 students (79% female, mean age = 21.6 years; 59% nursing students) participated. The median MHL score was 70 (range: 30-80). The linear regression model explained 17.5% of the variance in MHL. Higher MHL levels were associated with having the course as a first choice, holding a previous degree, reporting taking psychotropic medication use (which may reflect previous mental health service utilization), and higher levels of psychological well-being. Conclusions: This study provides evidence on factors associated with MHL among undergraduate health students, suggesting that higher MHL is associated with greater psychological well-being, highlighting the potential importance of integrating strategies to promote MHL and psychological well-being in health and nursing education. However, these findings should be interpreted with caution due to the single-institution convenience sample, potential self-selection and reporting biases, and cross-sectional design, which limits causal inferences.