Using Open-Ended Stressor Responses to Predict Depressive Symptoms across Demographics
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 9 of its 62 references that are in the map. First posted on arXiv 15 Nov 2022.
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References · 9
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- 2019Auditing and Achieving Intersectional Fairness in Classification Problemscited by 25
- 2021Gender and Racial Fairness in Depression Research using Social Mediacited by 17
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