Suppr超能文献

患者驱动的糖尿病技术:#WeAreNotWaiting 和 #OpenAPS 运动的情绪和人物。

Patient-Driven Diabetes Technologies: Sentiment and Personas of the #WeAreNotWaiting and #OpenAPS Movements.

机构信息

College of Nursing, University of Utah, Salt Lake City, USA.

University of Utah Health, Salt Lake City, USA.

出版信息

J Diabetes Sci Technol. 2020 Nov;14(6):990-999. doi: 10.1177/1932296820932928. Epub 2020 Jul 4.

Abstract

BACKGROUND

Patients with diabetes have developed innovative do-it-yourself (DIY) methods for adapting existing medical devices to better fit individual needs.

METHOD

A multiple method study used Symplur Analytics to analyze aggregated Twitter data of #WeAreNotWaiting and #OpenAPS tweets between 2014 and 2017 to examine DIY patient-led innovation. Conversation sentiment was examined between diabetes stakeholders to determine changes over time. Two hundred of the most shared photos were analyzed to understand visual representations of DIY patient-led innovations. Finally, discourse analysis was used to identify the personas who engage in DIY patient-led diabetes technologies activities and conversations on Twitter.

RESULTS

A total of 7886 participants who generated 46 578 tweets were included. Sentiment analysis showed that 82%-85% of interactions around DIY patient-led innovation was positive among patient/caregiver and physician groups. Through photo analysis, five content themes emerged: (1) disseminating media and conference coverage, (2) showcasing devices, (3) celebrating connections, (4) providing instructions, and (5) celebrating accomplishments. Six personas emerged across the overlapping userbase: (1) fearless leaders, (2) loopers living it up, (3) parents on a mission, (4) the tech titans, (5) movement supporters, and (6) healthcare provider advocates. Personas had varying goals and behaviors within the community.

CONCLUSIONS

#WeAreNotWaiting and #OpenAPS on Twitter reveal a fast-moving patient-led movement focused on DIY patient innovation that is further mobilized by an expanding and diverse userbase. Further research is indicated to bring technology savvy persons with diabetes into conversation with healthcare providers and researchers alike.

摘要

背景

糖尿病患者开发了创新的 DIY 方法,以适应现有医疗设备,更好地满足个人需求。

方法

采用多种方法研究,使用 Symplur Analytics 分析 2014 年至 2017 年#WeAreNotWaiting 和#OpenAPS 推文的聚合 Twitter 数据,以考察 DIY 患者主导的创新。考察糖尿病利益相关者之间的对话情绪,以确定随时间的变化。分析了 200 张最常分享的照片,以了解 DIY 患者主导创新的视觉表现。最后,采用话语分析来确定在 Twitter 上参与 DIY 患者主导的糖尿病技术活动和对话的角色。

结果

共纳入 7886 名参与者,产生了 46578 条推文。情绪分析显示,在患者/护理人员和医生群体中,82%-85%的 DIY 患者主导创新相关互动是积极的。通过照片分析,出现了五个内容主题:(1)传播媒体和会议报道,(2)展示设备,(3)庆祝联系,(4)提供指导,(5)庆祝成就。在重叠的用户群中出现了六个角色:(1)无畏的领导者,(2)快乐闭环者,(3)有使命的父母,(4)技术巨头,(5)运动支持者,(6)医疗保健提供者倡导者。角色在社区中具有不同的目标和行为。

结论

Twitter 上的#WeAreNotWaiting 和#OpenAPS 揭示了一个以 DIY 患者创新为重点的快速发展的患者主导运动,由不断扩大和多样化的用户群进一步推动。需要进一步研究,使具有糖尿病技术头脑的人能够与医疗保健提供者和研究人员进行对话。

相似文献

4
Do-It-Yourself (DIY) Systems in Diabetes: A Family and Provider Perspective.糖尿病的 DIY 系统:家庭和提供者的视角。
J Diabetes Sci Technol. 2020 Sep;14(5):917-921. doi: 10.1177/1932296820906204. Epub 2020 Mar 5.
5
Evolution of Do-It-Yourself Remote Monitoring Technology for Type 1 Diabetes.1 型糖尿病 DIY 远程监测技术的发展。
J Diabetes Sci Technol. 2020 Sep;14(5):854-859. doi: 10.1177/1932296819895537. Epub 2020 Jan 2.
6
Peer Mentoring in the Do-it-Yourself Artificial Pancreas System Community.同行指导在 DIY 人工胰腺系统社区中的应用。
J Diabetes Sci Technol. 2020 Nov;14(6):1022-1027. doi: 10.1177/1932296819883876. Epub 2019 Oct 24.

引用本文的文献

本文引用的文献

4
History and Perspective on DIY Closed Looping.DIY闭环的历史与展望
J Diabetes Sci Technol. 2019 Jul;13(4):790-793. doi: 10.1177/1932296818808307. Epub 2018 Oct 22.
7
Hacking diabetes: DIY artificial pancreas systems.攻克糖尿病:自制人工胰腺系统。
Lancet Diabetes Endocrinol. 2017 May;5(5):332. doi: 10.1016/S2213-8587(16)30397-7. Epub 2016 Nov 30.
8
Personas in online health communities.在线健康社区中的用户角色。
J Biomed Inform. 2016 Oct;63:212-225. doi: 10.1016/j.jbi.2016.08.019. Epub 2016 Aug 26.
10
Real-World Use of Open Source Artificial Pancreas Systems.开源人工胰腺系统的实际应用
J Diabetes Sci Technol. 2016 Nov 1;10(6):1411. doi: 10.1177/1932296816665635. Print 2016 Nov.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验