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
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 Matern...
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2021-04-01
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Series: | BMC Medical Informatics and Decision Making |
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Online Access: | https://doi.org/10.1186/s12911-021-01473-2 |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sujen Man Maharjan Anubhuti Poudyal Alastair van Heerden Prabin Byanjankar Ada Thapa Celia Islam Brandon A. Kohrt Ashley Hagaman |
spellingShingle |
Sujen Man Maharjan Anubhuti Poudyal Alastair van Heerden Prabin Byanjankar Ada Thapa Celia Islam Brandon A. Kohrt Ashley Hagaman 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 BMC Medical Informatics and Decision Making Adolescent Child health Depression Developing countries Digital health Digital phenotype |
author_facet |
Sujen Man Maharjan Anubhuti Poudyal Alastair van Heerden Prabin Byanjankar Ada Thapa Celia Islam Brandon A. Kohrt Ashley Hagaman |
author_sort |
Sujen Man Maharjan |
title |
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 |
title_short |
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 |
title_full |
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 |
title_fullStr |
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 |
title_full_unstemmed |
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 |
title_sort |
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 |
publisher |
BMC |
series |
BMC Medical Informatics and Decision Making |
issn |
1472-6947 |
publishDate |
2021-04-01 |
description |
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 |
topic |
Adolescent Child health Depression Developing countries Digital health Digital phenotype |
url |
https://doi.org/10.1186/s12911-021-01473-2 |
work_keys_str_mv |
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doaj-c0ce03cebe3448ceab262473cfeee2962021-04-11T11:38:08ZengBMCBMC Medical Informatics and Decision Making1472-69472021-04-0121111910.1186/s12911-021-01473-2Passive 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 acceptabilitySujen Man Maharjan0Anubhuti Poudyal1Alastair van Heerden2Prabin Byanjankar3Ada Thapa4Celia Islam5Brandon A. Kohrt6Ashley Hagaman7Transcultural Psychosocial Organization (TPO) NepalDivision of Global Mental Health, Department of Psychiatry and Behavioral Sciences, George Washington School of Medicine and Health SciencesCenter for Community Based Research, Human Sciences Research CouncilTranscultural Psychosocial Organization (TPO) NepalDivision of Global Mental Health, Department of Psychiatry and Behavioral Sciences, George Washington School of Medicine and Health SciencesGeorge Washington School of Medicine and Health SciencesDivision of Global Mental Health, Department of Psychiatry and Behavioral Sciences, George Washington School of Medicine and Health SciencesDepartment of Social and Behavioral Sciences, Yale School of Public Health, Yale UniversityAbstract 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): DERR1-10.2196/14734https://doi.org/10.1186/s12911-021-01473-2AdolescentChild healthDepressionDeveloping countriesDigital healthDigital phenotype |