Digital empowerment of dance movement therapy: innovative applications and evidence-based evaluation in mental health...

Mental health disorders are a severe global public health crisis. Dance movement therapy (DMT) offers unique benefits, but traditional DMT is limited by subjective evaluation, non-standardized protocols, and restricted access. Digital technologies such as virtual reality, artificial intelligence, and wearable sensors may address these limitations; however, a structural gap remains between technological application and rigorous clinical evidence.

This narrative review synthesizes literature from PubMed, Web of Science, Scopus, and CNKI. Sources used for population-specific synthesis were coded by population, intervention modality, outcome measures, study design, and relationship to the review question (direct digital-DMT; digital but non-DMT; conventional DMT/dance; mechanistic/contextual). Claims that extend beyond primary digital-DMT evidence are flagged as interpretive contributions or as findings from adjacent analogue sources.

Digital technologies can make DMT more multi-modal and quantitative, but direct trial evidence for digital DMT remains sparse and heterogeneous. Preliminary support for anxiety-related outcomes comes mainly from one small randomized trial of digital dance-art therapy and from mixed-methods online dance studies. Most population-specific estimates in this review derive from conventional (non-digital) DMT/dance syntheses or from digital but non-DMT analogues (for example, VR exposure therapy or home-based exergaming) and should not be read as direct digital-DMT effects. Conventional long-term dance/DMT programmes show modest cognitive improvements in older adults with mild cognitive impairment, while evidence for Alzheimer's disease remains inadequate. In China, Western theoretical frameworks and cultural constraints also limit localization.

Digital DMT requires deep interdisciplinary integration rather than simple technological combination. This review proposes a three-level localization framework for China and calls for large-sample randomized controlled trials, stronger data-privacy protections, and narrowed digital divides.