Internet of Things-Based Behavioral Intervention for Older Adults with Major Depressive Disorder: Preliminary Study

ABSTRACT

OBJECTIVE: To assess the effectiveness of Internet of Things (IoT)-based behavioral intervention for reducing depressive symptom of older adults with major depressive disorder. METHODS: A 12-week randomized cross-over controlled study was conducted at community mental health center. We recruited 39 participants with major depressive disorder aged 60 years or older. As a multidomain intervention, four evidence-based therapeutic factors (physical activity, healthy diet, social activity, and emotional regulation) were approached. To maintain motivation of participants, we applied contingency management using IoT device based on operant conditioning theory. RESULTS: The primary outcome was change of depressive symptom measured by Montgomery-Asberg Depression Rating Scale (MADRS). Mixed-effect model compared the effectiveness of intervention and usual care management (intervention by time and period interaction, p=0.017). And during the study period consisting of a total of visit 8, significant group difference was shown in post hoc test at visit 4 (MADRS score of intervention group MADRS score of control group=7.7±3.4 21.1±11.5, p=0.008). CONCLUSION: Community-implementable IoT-based behavioral intervention resulted in greater reduction of depressive symptom of elderly with major depressive disorder.