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  • What Happens in Peer-Support, Stays in Peer-Support: Software Architecture for Peer-Sourcing in Mental Health

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What Happens in Peer-Support, Stays in Peer-Support: Software Architecture for Peer-Sourcing in Mental Health

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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What Happens in Peer-Support, Stays in Peer-Support : Software Architecture for Peer-Sourcing in Mental Health. / Honary, Mahsa; Lee, Jaejoon; Bull, Christopher; Wang, Jiangtao; Helal, Sumi.

2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 2020. p. 644-653.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Honary, M, Lee, J, Bull, C, Wang, J & Helal, S 2020, What Happens in Peer-Support, Stays in Peer-Support: Software Architecture for Peer-Sourcing in Mental Health. in 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, pp. 644-653, IEEE Computer Society Signature Conference on Computers, Software and Applications (COMPSAC 2020), Madrid, Spain, 13/07/20. https://doi.org/10.1109/COMPSAC48688.2020.0-184

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@inproceedings{e93e694829e440869232b315084b75ff,
title = "What Happens in Peer-Support, Stays in Peer-Support: Software Architecture for Peer-Sourcing in Mental Health",
abstract = "Digital health technology utilizing wearables, IoT and mobile devices has been successfully applied in the monitoring of numerous diseases and conditions. However, intervention, in response to monitored data, is yet to benefit from technological support and continues to follow a traditional point-of-care delivery model by providers and health professionals. Mental health is an example of a critical health area in dire need for technology solutions to enable timely, effective and scalable interventions. This is especially the case with an increasing prevalence of mental health conditions and a declining capacity of the healthcare professional workforce. Numerous studies reveal the potential for peer support groups as an effective, scalable, cost-effective, first-line of response in mental health interventions. Peer support helps participants, at low and moderate risk, better understand their diseases or conditions and empowers them to take control of their own health. Peer support interactions also seems to inform health professionals with insights and intricate knowledge, making it effectively a learning health system. This paper proposes a software architecture to better enable {"}peer-sourcing{"}. We present related work and show how the proposed architecture might draw similarity to and differences from crowd-sourcing architectures. We also present a study in which we interacted with service users (mental health patients) and mental healthcare professionals to better understand and elicit the key requirements for the software architecture.",
keywords = "peer-sourcing, architecture, microservices, mental health, peer-support",
author = "Mahsa Honary and Jaejoon Lee and Christopher Bull and Jiangtao Wang and Sumi Helal",
year = "2020",
month = sep,
day = "22",
doi = "10.1109/COMPSAC48688.2020.0-184",
language = "English",
pages = "644--653",
booktitle = "2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)",
publisher = "IEEE",
note = "IEEE Computer Society Signature Conference on Computers, Software and Applications (COMPSAC 2020), COMPSAC ; Conference date: 13-07-2020 Through 17-07-2020",
url = "https://ieeecompsac.computer.org/2020/",

}

RIS

TY - GEN

T1 - What Happens in Peer-Support, Stays in Peer-Support

T2 - IEEE Computer Society Signature Conference on Computers, Software and Applications (COMPSAC 2020)

AU - Honary, Mahsa

AU - Lee, Jaejoon

AU - Bull, Christopher

AU - Wang, Jiangtao

AU - Helal, Sumi

PY - 2020/9/22

Y1 - 2020/9/22

N2 - Digital health technology utilizing wearables, IoT and mobile devices has been successfully applied in the monitoring of numerous diseases and conditions. However, intervention, in response to monitored data, is yet to benefit from technological support and continues to follow a traditional point-of-care delivery model by providers and health professionals. Mental health is an example of a critical health area in dire need for technology solutions to enable timely, effective and scalable interventions. This is especially the case with an increasing prevalence of mental health conditions and a declining capacity of the healthcare professional workforce. Numerous studies reveal the potential for peer support groups as an effective, scalable, cost-effective, first-line of response in mental health interventions. Peer support helps participants, at low and moderate risk, better understand their diseases or conditions and empowers them to take control of their own health. Peer support interactions also seems to inform health professionals with insights and intricate knowledge, making it effectively a learning health system. This paper proposes a software architecture to better enable "peer-sourcing". We present related work and show how the proposed architecture might draw similarity to and differences from crowd-sourcing architectures. We also present a study in which we interacted with service users (mental health patients) and mental healthcare professionals to better understand and elicit the key requirements for the software architecture.

AB - Digital health technology utilizing wearables, IoT and mobile devices has been successfully applied in the monitoring of numerous diseases and conditions. However, intervention, in response to monitored data, is yet to benefit from technological support and continues to follow a traditional point-of-care delivery model by providers and health professionals. Mental health is an example of a critical health area in dire need for technology solutions to enable timely, effective and scalable interventions. This is especially the case with an increasing prevalence of mental health conditions and a declining capacity of the healthcare professional workforce. Numerous studies reveal the potential for peer support groups as an effective, scalable, cost-effective, first-line of response in mental health interventions. Peer support helps participants, at low and moderate risk, better understand their diseases or conditions and empowers them to take control of their own health. Peer support interactions also seems to inform health professionals with insights and intricate knowledge, making it effectively a learning health system. This paper proposes a software architecture to better enable "peer-sourcing". We present related work and show how the proposed architecture might draw similarity to and differences from crowd-sourcing architectures. We also present a study in which we interacted with service users (mental health patients) and mental healthcare professionals to better understand and elicit the key requirements for the software architecture.

KW - peer-sourcing

KW - architecture

KW - microservices

KW - mental health

KW - peer-support

U2 - 10.1109/COMPSAC48688.2020.0-184

DO - 10.1109/COMPSAC48688.2020.0-184

M3 - Conference contribution/Paper

SP - 644

EP - 653

BT - 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)

PB - IEEE

Y2 - 13 July 2020 through 17 July 2020

ER -