Gemza Ademaj

Doktorand

Designing Support for Sensemaking in Multimodal, Multi-model Mental Health Assessments

Författare

Gemza Ademaj
Xinyuan Zhang
Ahmed Abbasi
Saonee Sarker
Suprateek Sarker

Summary, in English

Mental health assessments increasingly rely on remote formats that produce rich but complex multimodal data in the form of text, audio, and video, processed through multiple machine learning models. While these environments offer new opportunities for insight, they also pose significant challenges for effective clinical sensemaking. This study introduces a dashboard designed to address these challenges by enabling practitioners to explore behavioral data from multiple angles while mitigating overreliance on model accuracy metrics. Grounded in the Design Science Research, the dashboard design is informed by an integration of Integrative Sensemaking Theory and Signal Detection Theory. The research contributes a set of design requirements for supporting sensemaking in multimodal, multi-model contexts, instantiates them in a dashboard artifact, and proposes an evaluation with practitioners using clinically grounded sensemaking tasks. This work advances computational design by offering theoretical and practical insights for advancing the integration of these complex data in mental healthcare context.

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