[Purpose/significance] By constructing a multi-level driving model, this study systematically analyzes the
topological relationships and action pathways of driving factors influencing mobile short video users' digital detox be⁃
haviors, aiming to provide a research paradigm with both theoretical explanatory power and practical applicability for
the digital health ecosystem. [Method/process] First, grounded theory analysis was employed to identify key factors af⁃
fecting users' digital detox behaviors. Second, the ADSM was applied to categorize these factors hierarchically and ex⁃
plore their transmission paths, revealing interrelationships among them. Finally, the MICMAC algorithm was used to
classify the influencing factors into clusters and validate the effectiveness and reliability of the constructed model. [Re⁃
sult/conclusion] The results indicate that the counter-dependency model of mobile short video users' digital disen⁃
gagement behaviors can be divided into seven hierarchical levels. The twelve driving factors are further classified into
three clusters: dependent clusters, autonomous clusters, and driving clusters. Among them, self-regulation capability is
identified as the most fundamental driver influencing digital detox behaviors.