Integration of passive sensing technology to enhance delivery of psychological interventions for mothers with depression: the StandStrong study

Abstract

Abstract Psychological interventions delivered by non-specialist providers have shown mixed results for treating maternal depression. mHealth solutions hold the possibility for unobtrusive behavioural data collection to identify challenges and reinforce change in psychological interventions. We conducted a proof-of-concept study using passive sensing integrated into a depression intervention delivered by non-specialists to twenty-four adolescents and young mothers (30% 15–17 years old; 70% 18–25 years old) with infants (< 12 months old) in rural Nepal. All mothers showed a reduction in depression symptoms as measured with the Beck Depression Inventory. There were trends toward increased movement away from the house (greater distance measured through GPS data) and more time spent away from the infant (less time in proximity measured with the Bluetooth beacon) as the depression symptoms improved. There was considerable heterogeneity in these changes and other passively collected data (speech, physical activity) throughout the intervention. This proof-of-concept demonstrated that passive sensing can be feasibly used in low-resource settings and can personalize psychological interventions. Care must be taken when implementing such an approach to ensure confidentiality, data protection, and meaningful interpretation of data to enhance psychological interventions.