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

Journal: Scientific reports

Volume: 14

Issue: 1

Year of Publication: 2024

Affiliated Institutions:  Center for Community Based Research, Human Sciences Research Council, Pietermaritzburg, South Africa. avanheerden@hsrc.ac.za. Department of Sociomedical Sciences, Columbia Mailman School of Public Health, New York, NY, USA. Department of Social and Behavioral Sciences, Yale School of Public Health, Yale University, New Haven, CT, USA. Transcultural Psychosocial Organization Nepal, Kathmandu, Nepal. Department for Global Health and Social Medicine, Kings College London, London, UK. Division of Global Health Equity, Brigham and Women's Hospital Boston, Boston, MA, USA. Department of Psychiatry and Behavioral Sciences, Center for Global Mental Health Equity, George Washington School of Medicine and Health Sciences, Washington, DC, USA.

Abstract summary 

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.

Authors & Co-authors:  van Heerden Alastair A Poudyal Anubhuti A Hagaman Ashley A Maharjan Sujen Man SM Byanjankar Prabin P Bemme Dörte D Thapa Ada A Kohrt Brandon A BA

Study Outcome 

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Statistics
Citations :  Baron EC, et al. Maternal mental health in primary care in five low-and middle-income countries: A situational analysis. BMC Health Serv. Res. 2016;16:1–16. doi: 10.1186/s12913-016-1291-z.
Authors :  8
Identifiers
Doi : 13535
SSN : 2045-2322
Study Population
Mothers
Mesh Terms
Humans
Other Terms
Study Design
Study Approach
Mixed Methods
Country of Study
Publication Country
England