Micro-costing analysis reveals significant cost reductions for digital mental health in adolescents, highlighting feasibility in resource-constrained settings.
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.
No takes yet. Share an insight, caveat, or question.
Gunisetty et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: