Economic Evaluation of a Digital Psychobehavioral Intervention for Chronic Inflammatory Skin Disease (MindMySkin): Protocol for a Trial-Based Cost-Effectiveness Analysis.

Background: Digital mental health apps are increasingly available and used, yet the large majority lack clinical and economic evidence, limiting reimbursement support and the identification of high-value interventions. MindMySkin is a digital psychobehavioral mobile intervention co-designed with patients and guided by behavioral change frameworks to address the psychobehavioral determinants of symptom burden in chronic inflammatory skin diseases. The app comprises 74 modules targeting illness coherence, symptom management, and emotional and functional impairment and is currently being tested in a double-blind randomized controlled trial. Objective: This protocol prespecifies an economic evaluation plan conducted as a secondary analysis alongside the trial to assess the cost-effectiveness of MindMySkin within Singapore's health care system. Methods: The parent trial recruits English-speaking participants aged 16 years or older with psoriasis, eczema, or chronic urticaria across 3 sites in Singapore (target N=690; 2:1 allocation, 32-week follow-up). The active comparator is Healthy365, a general wellness app managed by the Singapore Health Promotion Board. The trial-based economic evaluation will adopt a health care system perspective as the primary analytic viewpoint. Resource costs will include intervention deployment and dermatology-related health care use. Indirect medical costs and work productivity losses will additionally be included in a sensitivity analysis conducted from a societal perspective. A cost-effectiveness analysis will use the Dermatology Life Quality Index, a dermatology-specific measure of health-related quality of life, while a cost-utility analysis will derive health utilities from the EQ-5D-5L to enable estimation of quality-adjusted life years. Incremental cost-effectiveness ratios and net monetary benefit will be estimated using intention-to-treat analyses with regression adjustment. Uncertainty will be explored using bootstrapping, deterministic sensitivity analyses, subgroup analyses, and scenario modeling. A Markov model-based extrapolation over 5 years will be undertaken if within-trial results suggest a high likelihood of cost-effectiveness. Results: Study funding is provided by the National Medical Research Council Clinical-Scientist Individual Research Grant New Investigator Grant (CS-IRG NIG; funded on June 5, 2024), and ethics approval has been obtained (2022/00751). Recruitment commenced in February 2026, and as of June 2026, a total of 46 participants have been enrolled. Economic data collection will be conducted concurrently with the parent trial, and the economic analysis is expected to commence following trial completion, which is anticipated in 2028. Conclusions: By embedding a health economic evaluation within a randomized controlled design and incorporating condition-sensitive outcome measures, this study advances methodological standards for evaluating scalable psychobehavioral interventions. Demonstrating value through disability reduction rather than survival gain may strengthen the legitimacy of low-intensity digital therapeutics within health technology assessment frameworks and inform implementation decisions in resource-constrained health systems.