Using Open-Ended Stressor Responses to Predict Depressive Symptoms across Demographics

Carlos Aguirre; Mark Dredze; Philip Resnik

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arXiv · 2211.07932

Using Open-Ended Stressor Responses to Predict Depressive Symptoms across Demographics

Carlos Aguirre·Mark Dredze·Philip Resnik

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Abstract

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.

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Carlos Aguirre, Mark Dredze, Philip Resnik. 2022-11-15. Using Open-Ended Stressor Responses to Predict Depressive Symptoms across Demographics. https://arxiv.org/abs/2211.07932

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