Passive sensing technology was integrated into a psychological intervention for maternal depression in rural Nepal, targeting 24 adolescent and young mothers. This proof-of-concept study assessed the feasibility of using mHealth solutions for unobtrusive behavioral data collection to enhance non-specialist-delivered interventions. All participants, aged 15-25 with infants under 12 months, showed a reduction in depression symptoms as measured by the Beck Depression Inventory. Trends indicated increased movement away from the home (tracked via GPS) and more time spent away from their infants (measured by Bluetooth proximity) as symptoms improved. However, there was significant variability in passive data, such as speech and physical activity, across individuals. The study demonstrates the feasibility of passive sensing in low-resource settings, offering potential for personalized interventions, though it emphasizes the importance of data protection, confidentiality, and careful interpretation of behavioral data.