  This study explores the intersection of information technology-based
self-monitoring (ITSM) and emotional responses in chronic care. It critiques
the lack of theoretical depth in current ITSM research and proposes a dynamic
emotion process theory to understand ITSM's impact on users' emotions.
Utilizing computational grounded theory and machine learning analysis of
hypertension app reviews, the research seeks to extend emotion theory by
examining ITSM stimuli and their influence on emotional episodes, moving beyond
discrete emotion models towards a continuous, nuanced understanding of
emotional responses.
