Micro-costing analysis of a digital mental health intervention for adolescents in south India: the AikyaMind mHealth application
DOI:
https://doi.org/10.18203/2394-6040.ijcmph20252846Keywords:
Adolescent mental health, Cost-effectiveness, Digital health economics, India, mHealth, Micro-costingAbstract
Background: Adolescent mental health disorders affect 7.3% of Indian youth, yet treatment remains inaccessible for over 80%. While digital interventions show promise, their economic feasibility in resource-constrained settings remains unexplored. This study conducted a micro-costing analysis of AikyaMind, a comprehensive mHealth application for adolescent mental health in Karnataka, India.
Methods: Using the activity-based costing-ingredients methodology, we analyzed costs from a provider’s perspective over a one-year implementation period (2023-24). Data collection employed structured micro-costing tools capturing direct development, meeting, and training costs. Capital items were annualized using a 3% discount rate. Per-user costs were calculated across utilization scenarios (100-10,000 users). Fiscal impact was assessed against Karnataka’s District Mental Health Program budget. One-way sensitivity analysis identified cost drivers.
Results: Total costs were ₹74,548 (US$896), comprising direct development (65.73%), meetings (26.84%), and training (7.43%). App development represented the largest component (₹30,000). Per-user costs demonstrated substantial economies of scale, decreasing from ₹745.48 (100 users) to ₹7.45 (10,000 users)- a 99% reduction. Implementation required only 0.07% of the state mental health budget. Sensitivity analysis revealed that app development costs were the primary driver, causing a variation of ±₹6,000 with a 20% change.
Conclusions: The AikyaMind application demonstrates exceptional economic feasibility for addressing adolescent mental health gaps in LMICs. With a total development cost of less than US$900 and a cost of US$0.09 per user at scale, digital mental health interventions offer financially viable solutions for resource-constrained settings. These findings support the integration of mHealth within existing public health programs to achieve universal health coverage goals.
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