  Stressors are related to depression, but this relationship is complex. We
investigate the relationship between open-ended text responses about stressors
and depressive symptoms across gender and racial/ethnic groups. First, we use
topic models and other NLP tools to find thematic and vocabulary differences
when reporting stressors across demographic groups. We train language models
using self-reported stressors to predict depressive symptoms, finding a
relationship between stressors and depression. Finally, we find that
differences in stressors translate to downstream performance differences across
demographic groups.
