How do machine learning models perform in the detection of depression, anxiety, and stress among undergraduate students? A systematic review.

Undergraduate students are often impacted by depression, anxiety, and stress. In this context, machine learning may support mental health assessment. Based on the following research question: "How do machine learning models perform in the detection of depression, anxiety, and stress among undergraduate students?", we aimed to evaluate the performance of these models.

Association of Emotional Self-Regulation with Psychological Distress and Positive Functioning Dimensions in Brazilian University Students during the COVID-19 Pandemic.

Emotional self-regulation is a relevant factor for human development capable of minimizing emotional difficulties in the face of adverse events, as was particularly useful during the COVID-19 pandemic. The present study aimed to evaluate emotional self-regulation in Brazilian health science university students and its relationship with positive psychology constructs (subjective well-being, hope, optimism, spirituality, self-compassion, and self-efficacy) and psychological distress (depression, anxiety, and stress). This was a prospective, cross-sectional, observational, analytic study of 1062 Brazilian undergraduate students with data collected using self-administered online questionnaires.