Background Burnout is a pervasive issue among medical students, exhibiting a high prevalence that jeopardizes their academic success and may also predispose them to more severe affective disorders such as depression. This study aims to explore the complex relationships between psychological capital (PsyCap), general social support, educational satisfaction, and burnout, and how these factors collectively influence dropout intentions.

Methods
A non-probabilistic convenience sample was collected through an online survey from first- and second-year medical students at a Faculty of Medicine in Portugal. The survey employed psychometric instruments to measure burnout (BAT-12), social support (F-SozU K-6), PsyCap (CPC-12R), satisfaction with education, and dropout intentions (Screening Instrument for Students At-Risk of Dropping Out). Structural equation modeling was applied to analyze the data from 351 participants.

Results
The model demonstrated a significant positive association between burnout and dropout intentions ( = 0.37; p < 0.001), underscoring burnout as a direct correlate of dropout intentions alongside educational satisfaction ( = −0.25; p = 0.003) and PsyCap ( = −0.22; p = 0.005). Higher social support is associated with reduced burnout ( = −0.28; p < 0.001) and increased educational satisfaction ( = 0.22; p = 0.002).

Limitations
The non-probabilistic sampling method prevents the generalization of the findings. The cross-sectional data do not permit the inference of temporal relationships between the studied variables.

Conclusions
These findings emphasize the importance that burnout may have on dropout intentions, and contribute to the understanding of affective syndromes such as burnout in educational settings.

Background Depression, anxiety, and stress (DAS) have been linked to poor academic outcomes. This study explores the relationships among DAS, academic engagement, dropout intentions, and academic performance — measured by Grade Point Average (GPA) — in medical students. It aims to understand how these factors relate to each other and predict academic performance.