Investigating the Data Management Practices of Predictive Mental Health Researchers
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Eickman, William Randall
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Abstract
The integration of technology in mental health research holds signif-
icant promise but introduces complex ethical considerations around
data management. This paper explores the current practices of com-
puting researchers working with mental health data, particularly
focusing on their data management approaches, methodological
transparency, and institutional guidance. Through interviews with
computing researchers who have developed predictive or generative
systems for mental health applications, we identify key challenges
including inconsistent IRB protocols, unclear guidelines for non-
clinical mental health data, fragmentation across disciplines, and
varied approaches to transparency. Our findings highlight opportu-
nities for better collaborative data management between computing
researchers and mental health professionals, as well as the need for
clearer critical data education. This research contributes insights
toward developing standardized practices in a rapidly evolving
interdisciplinary field.
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Undergraduate Research Option Thesis