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Utilizing passive sensing data to provide personalized psychological care in low-resource settings
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940775/ https://www.ncbi.nlm.nih.gov/pubmed/33709058 http://dx.doi.org/10.12688/gatesopenres.13117.2 |
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author | Byanjankar, Prabin Poudyal, Anubhuti Kohrt, Brandon A Maharjan, Sujen Man Hagaman, Ashley van Heerden, Alastair |
author_facet | Byanjankar, Prabin Poudyal, Anubhuti Kohrt, Brandon A Maharjan, Sujen Man Hagaman, Ashley van Heerden, Alastair |
author_sort | Byanjankar, Prabin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7940775 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-79407752021-03-10 Utilizing passive sensing data to provide personalized psychological care in low-resource settings Byanjankar, Prabin Poudyal, Anubhuti Kohrt, Brandon A Maharjan, Sujen Man Hagaman, Ashley van Heerden, Alastair Gates Open Res Software Tool Article 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. F1000 Research Limited 2021-03-02 /pmc/articles/PMC7940775/ /pubmed/33709058 http://dx.doi.org/10.12688/gatesopenres.13117.2 Text en Copyright: © 2021 Byanjankar P et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Tool Article Byanjankar, Prabin Poudyal, Anubhuti Kohrt, Brandon A Maharjan, Sujen Man Hagaman, Ashley van Heerden, Alastair Utilizing passive sensing data to provide personalized psychological care in low-resource settings |
title | Utilizing passive sensing data to provide personalized psychological care in low-resource settings |
title_full | Utilizing passive sensing data to provide personalized psychological care in low-resource settings |
title_fullStr | Utilizing passive sensing data to provide personalized psychological care in low-resource settings |
title_full_unstemmed | Utilizing passive sensing data to provide personalized psychological care in low-resource settings |
title_short | Utilizing passive sensing data to provide personalized psychological care in low-resource settings |
title_sort | utilizing passive sensing data to provide personalized psychological care in low-resource settings |
topic | Software Tool Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940775/ https://www.ncbi.nlm.nih.gov/pubmed/33709058 http://dx.doi.org/10.12688/gatesopenres.13117.2 |
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