scholarly journals Passive sensing on mobile devices to improve mental health services with adolescent and young mothers in low-resource settings: the role of families in feasibility and acceptability 

2020 ◽  
Author(s):  
Sujen Man Maharjan ◽  
Anubhuti Poudyal ◽  
Alastair van Heerden ◽  
Prabin Byanjankar ◽  
Ada Thapa ◽  
...  
Keyword(s):  
Data Collection ◽  
Health Services ◽  
Mobile Devices ◽  
Family Involvement ◽  
Mobile Phones ◽  
Young Mothers ◽  
Low Resource Settings ◽  
Low Resource ◽  
Passive Sensing ◽  
Passive Data

Abstract Background: Passive sensor data from mobile devices can shed light on daily activities, social behavior, and maternal-child interactions to improve maternal and child health services including mental healthcare. We assessed feasibility and acceptability of the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) platform. The StandStrong passive data collection was piloted with adolescent and young mothers, including mothers experiencing postpartum depression, in Nepal.Methods: Mothers (15-25 years old) with infants (<12 months old) were recruited in person from vaccination clinics in rural Nepal. They were provided with an Android smartphone and a Bluetooth beacon to collect data in four domains: the mother’s location using the Global Positioning System (GPS), physical activity using the phone’s accelerometer, auditory environment using episodic audio recording on the phone, and mother-infant proximity measured with the Bluetooth beacon attached to the infant’s clothing. Feasibility and acceptability were evaluated based on the amount of passive sensing data collected compared to the total amount that could be collected in a 2-week period. Endline qualitative interviews (n=31) were conducted to understand mothers’ experiences and perceptions of passive data collection. Results: 782 women were approached and 320 met eligibility criteria. 38 mothers (11 depressed, 27 non-depressed) were enrolled. Of 9,605 possible readings per sensor, 5,579 audio recordings [mean (M)=57.4%; median (Mdn)=62.6%], 5,001 activity readings (M=50.6%; Mdn=63.2%), 4,168 proximity readings (M=41.1%; Mdn=47.6%), and 3,482 GPS readings (M=35.4%; Mdn=39.2%) were obtained. Feasibility challenges were phone battery charging, data usage exceeding pre-paid limits, and burden of carrying mobile phones. Acceptability challenges were privacy concerns and lack of family involvement. Overall, families’ understanding of passive sensing and families’ awareness of potential benefits to mothers and infants were the major modifiable factors to increase acceptability and reduce gaps in data collection. Conclusion: Approximately half of all possible passive data readings were collected. Feasibility challenges can be addressed by providing alternative phone charging options, setting up reverse billing for the app, and exploring smartwatches as a replacement for mobile phones. Enhancing acceptability will require greater family involvement and improved communication regarding benefits of passive sensing for psychological interventions and other health services. Registration: International Registered Report Identifier (IRRID): DERR1-10.2196/14734

scholarly journals Passive sensing on mobile devices to improve mental health services with adolescent and young mothers in low-resource settings: the role of families in feasibility and acceptability

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sujen Man Maharjan ◽  
Anubhuti Poudyal ◽  
Alastair van Heerden ◽  
Prabin Byanjankar ◽  
Ada Thapa ◽  
...  
Keyword(s):  
Data Collection ◽  
Health Services ◽  
Mobile Devices ◽  
Family Involvement ◽  
Mobile Phones ◽  
Young Mothers ◽  
Audio Recording ◽  
Low Resource Settings ◽  
Passive Sensing ◽  
Passive Data

Abstract Background Passive sensor data from mobile devices can shed light on daily activities, social behavior, and maternal-child interactions to improve maternal and child health services including mental healthcare. We assessed feasibility and acceptability of the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) platform. The StandStrong passive data collection platform was piloted with adolescent and young mothers, including mothers experiencing postpartum depression, in Nepal. Methods Mothers (15–25 years old) with infants (< 12 months old) were recruited in person from vaccination clinics in rural Nepal. They were provided with an Android smartphone and a Bluetooth beacon to collect data in four domains: the mother’s location using the Global Positioning System (GPS), physical activity using the phone’s accelerometer, auditory environment using episodic audio recording on the phone, and mother-infant proximity measured with the Bluetooth beacon attached to the infant’s clothing. Feasibility and acceptability were evaluated based on the amount of passive sensing data collected compared to the total amount that could be collected in a 2-week period. Endline qualitative interviews were conducted to understand mothers’ experiences and perceptions of passive data collection. Results Of the 782 women approached, 320 met eligibility criteria and 38 mothers (11 depressed, 27 non-depressed) were enrolled. 38 mothers (11 depressed, 27 non-depressed) were enrolled. Across all participants, 5,579 of the hour-long data collection windows had at least one audio recording [mean (M) = 57.4% of the total possible hour-long recording windows per participant; median (Mdn) = 62.6%], 5,001 activity readings (M = 50.6%; Mdn = 63.2%), 4,168 proximity readings (M = 41.1%; Mdn = 47.6%), and 3,482 GPS readings (M = 35.4%; Mdn = 39.2%). Feasibility challenges were phone battery charging, data usage exceeding prepaid limits, and burden of carrying mobile phones. Acceptability challenges were privacy concerns and lack of family involvement. Overall, families’ understanding of passive sensing and families’ awareness of potential benefits to mothers and infants were the major modifiable factors increasing acceptability and reducing gaps in data collection. Conclusion Per sensor type, approximately half of the hour-long collection windows had at least one reading. Feasibility challenges for passive sensing on mobile devices can be addressed by providing alternative phone charging options, reverse billing for the app, and replacing mobile phones with smartwatches. Enhancing acceptability will require greater family involvement and improved communication regarding benefits of passive sensing for psychological interventions and other health services. Registration International Registered Report Identifier (IRRID): DERR1-10.2196/14734

scholarly journals Passive Sensing Data Collection with Adolescent Mothers and Their Infants to Improve Mental Health Services in Low-Resource Settings: A Feasibility and Acceptability Study in Rural Nepal

2020 ◽  
Author(s):  
Sujen Man Maharjan ◽  
Anubhuti Poudyal ◽  
Alastair van Heerden ◽  
Prabin Byanjankar ◽  
Ada Thapa ◽  
...  
Keyword(s):  
Data Collection ◽  
Health Services ◽  
Family Involvement ◽  
Mobile Phones ◽  
Qualitative Interviews ◽  
Low Resource Settings ◽  
Sensing Data ◽  
Passive Sensing ◽  
Passive Data ◽  
Rural Nepal

Abstract Background: Passive sensor data from mobile phones can shed light on daily activities, social behavior, and maternal-child interactions to improve maternal and child health services including mental healthcare. Our Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) study assessed feasibility and acceptability of passive data collection with young mothers, including mothers experiencing postpartum depression, in rural Nepal.Methods: Mothers between 15-25 years of age with infants less than 12 months old were recruited from vaccination clinics in rural Nepal. They were provided with a mobile smartphone and passive Bluetooth beacon to collect data in four domains: the mother’s location using the Global Positioning System (GPS), physical activity using the phone’s accelerometer, auditory environment using episodic audio recording on the phone, and mother-infant proximity measured with Bluetooth beacon attached to the infant’s clothing. Feasibility and acceptability were evaluated based on the amount of passive sensing data collected compared to the total amount that could be collected in a 2-week period. End-line qualitative interviews (n=31) were conducted to understand mothers’ experiences and perceptions of passive data collection.Results: 782 women were approached and 320 met eligibility criteria. 38 mothers (11 depressed, 27 non-depressed) were enrolled. Of 9,602 possible readings per sensor, 57.4% of audio (5,579 recordings), 50.6% of activity (5,001 readings), 41.1% of proximity (4,168 readings), and 35.4% of GPS (3,482 readings) were obtained. The percentage of data collection was comparable for depressed and non-depressed mothers. Qualitative interviews revealed mobile charging, excessive data usage, and burden of carrying mobile phones as feasibility challenges. Concerns for privacy and family involvement were acceptability challenges. Overall, study team engagement and education of family members on technology contributed to mothers’ comfort participating in passive data collection. Conclusion: Approximately half of all possible passive data were collected. Feasibility challenges can be addressed by providing alternative phone charging options, setting up reverse billing for the app, and exploring smartwatches as replacement for mobile phones. Enhancing acceptability will require greater family involvement and improved communication regarding benefits of passive sensing data collection for psychological treatments and other health services. Registration: International Registered Report Identifier (IRRID): DERR1-10.2196/14734

scholarly journals Tuberculosis: an opportunity to integrate mental health services in primary care in low-resource settings

2018 ◽  
Vol 5 (12) ◽  
pp. 952-954 ◽  
Author(s):  
Annika C Sweetland ◽  
Ernesto Jaramillo ◽  
Milton L Wainberg ◽  
Neerja Chowdhary ◽  
Maria A Oquendo ◽  
...  
Keyword(s):  
Mental Health ◽  
Primary Care ◽  
Mental Health Services ◽  
Health Services ◽  
Low Resource Settings ◽  
Low Resource

scholarly journals Utilizing passive sensing data to provide personalized psychological care in low-resource settings

2021 ◽  
Vol 4 ◽  
pp. 118
Author(s):  
Prabin Byanjankar ◽  
Anubhuti Poudyal ◽  
Brandon A Kohrt ◽  
Sujen Man Maharjan ◽  
Ashley Hagaman ◽  
...  
Keyword(s):  
Mental Health ◽  
Adolescent Mothers ◽  
Behavioral Patterns ◽  
Proximity Data ◽  
Low Resource Settings ◽  
Lay Counselors ◽  
Sensing Data ◽  
Low Resource ◽  
Counseling Intervention ◽  
Passive Sensing

Background: With the growing ubiquity of smartphones and wearable devices, there is an increased potential of collecting passive sensing data in mobile health. Passive data such as physical activity, Global Positioning System (GPS), interpersonal proximity, and audio recordings can provide valuable insight into the lives of individuals. In mental health, these insights can illuminate behavioral patterns, creating exciting opportunities for mental health service providers and their clients to support pattern recognition and problem identification outside of formal sessions. In the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) project, our aim was to build an mHealth application to facilitate the delivery of psychological treatments by lay counselors caring for adolescent mothers with depression in Nepal. Methods: This paper describes the development of the StandStrong platform comprising the StandStrong Counselor application, and a cloud-based processing system, which can incorporate any tool that generates passive sensing data. We developed the StandStrong Counselor application that visualized passively collected GPS, proximity, and activity data. In the app, GPS data displays as heat maps, proximity data as charts showing the mother and child together or apart, and mothers’ activities as activity charts. Lay counselors can use the StandStrong application during counseling sessions to discuss mothers’ behavioral patterns and clinical progress over the course of a five-week counseling intervention. Achievement Awards based on collected data can also be automatically generated and sent to mothers. Additionally, messages can be sent from counselors to mother’s personal phones through the StandStrong platform. Discussion: The StandStrong platform has the potential to improve the quality and effectiveness of psychological services delivered by non-specialists in diverse global settings.

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