SOMAScience: A Novel Platform for Multidimensional, Longitudinal Pain Assessment.
SOMAScience: A Novel Platform for Multidimensional, Longitudinal Pain Assessment.
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SOMAScience：多维纵向疼痛评估的新平台。
DOI：
10.2196/47177
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发表时间：
2024-01-12
影响因子：
5
通讯作者：
Petzschner, Frederike H.
中科院分区：
文献类型：
--
作者：
Gunsilius, Chloe Zimmerman;Heffner, Joseph;Bruinsma, Sienna;Corinha, Madison;Cortinez, Maria;Dalton, Hadley;Duong, Ellen;Lu, Joshua;Omar, Aisulu;Owen, Lucy Long Whittington;Roarr, Bradford Nazario;Tang, Kevin;Petzschner, Frederike H.
关键词：
慢性疼痛是美国最重要的健康问题之一，影响着超过20%的人口。尽管它对日益严重的健康危机做出了贡献，但缺乏对疾病发展、进展或治疗结果的可靠预测。自我报告仍然是评估疼痛的最有效方法，但测量通常是在很短的时间窗口内在稀疏的环境中获得的，限制了它们的预测能力。在本文中，我们提出了一个新的移动健康平台SOMAScience。SOMAScience是科学家和临床医生易于使用的研究工具，通过促进纵向、多维、自我报告的疼痛数据的获取、传输和分析，能够在单中心和多中心研究中收集大规模疼痛数据集。SOMAScience的数据采集是通过用户友好的智能手机应用程序SOMA完成的，该应用程序使用体验采样方法来捕获对疼痛强度、不适、干扰、位置、情绪、活动和对第二天的预测的瞬时和每日评估，从而为日常疼痛动态提供个人见解。随着时间的推移，数据及其趋势的可视化意味着个人用户能够自我管理他们的痛苦。本文概述了SOMAScience发展中涉及的科学、临床、技术和用户考虑，以及如何将其用于临床研究或疼痛自我管理目的。我们的目标是为SOMAScience为个人用户提供一个急需的平台，以深入了解他们疼痛的多维特征，同时降低研究人员和临床医生获取疼痛数据类型的门槛，最终改善慢性疼痛的预防、诊断和治疗。
Chronic pain is one of the most significant health issues in the United States, affecting more than 20% of the population. Despite its contribution to the increasing health crisis, reliable predictors of disease development, progression, or treatment outcomes are lacking. Self-report remains the most effective way to assess pain, but measures are often acquired in sparse settings over short time windows, limiting their predictive ability. In this paper, we present a new mobile health platform called SOMAScience. SOMAScience serves as an easy-to-use research tool for scientists and clinicians, enabling the collection of large-scale pain datasets in single- and multicenter studies by facilitating the acquisition, transfer, and analysis of longitudinal, multidimensional, self-report pain data. Data acquisition for SOMAScience is done through a user-friendly smartphone app, SOMA, that uses experience sampling methodology to capture momentary and daily assessments of pain intensity, unpleasantness, interference, location, mood, activities, and predictions about the next day that provide personal insights into daily pain dynamics. The visualization of data and its trends over time is meant to empower individual users’ self-management of their pain. This paper outlines the scientific, clinical, technological, and user considerations involved in the development of SOMAScience and how it can be used in clinical studies or for pain self-management purposes. Our goal is for SOMAScience to provide a much-needed platform for individual users to gain insight into the multidimensional features of their pain while lowering the barrier for researchers and clinicians to obtain the type of pain data that will ultimately lead to improved prevention, diagnosis, and treatment of chronic pain.
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影响因子：
1.3
作者：
Booth, John;Moseley, G. Lorimer;Hubscher, Markus
通讯作者：
Hubscher, Markus
影响因子：
9.9
作者：
Cook, Karon F.;Dunn, Winnie;Gershon, Richard C.
通讯作者：
Gershon, Richard C.
影响因子：
4
作者：
Chapman, C. Richard;Donaldson, Gary W.;Bradshaw, David H.
通讯作者：
Bradshaw, David H.
DOI：
10.1002/ejp.1688
发表时间：
2021-03
期刊：
European journal of pain (London, England)
影响因子：
--
作者：
Ali SM;Lau WJ;McBeth J;Dixon WG;van der Veer SN
通讯作者：
van der Veer SN
影响因子：
2.6
作者：
Caseiro, Marilia;Woznowski-Vu, Arthur;Wideman, Timothy H.
通讯作者：
Wideman, Timothy H.