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基于应用程序的干预措施,以支持 COVID-19 大流行期间的急救人员和一线工作者:需求评估和混合方法实施研究。

An App-Based Intervention to Support First Responders and Essential Workers During the COVID-19 Pandemic: Needs Assessment and Mixed Methods Implementation Study.

机构信息

Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, CA, United States.

College of Liberal Arts and Sciences, University of Iowa, Iowa City, IA, United States.

出版信息

J Med Internet Res. 2021 May 20;23(5):e26573. doi: 10.2196/26573.

Abstract

BACKGROUND

The COVID-19 pandemic has created unprecedented challenges for first responders (eg, police, fire, and emergency medical services) and nonmedical essential workers (eg, workers in food, transportation, and other industries). Health systems may be uniquely suited to support these workers given their medical expertise, and mobile apps can reach local communities despite social distancing requirements. Formal evaluation of real-world mobile app-based interventions is lacking.

OBJECTIVE

We aimed to evaluate the adoption, acceptability, and appropriateness of an academic medical center-sponsored app-based intervention (COVID-19 Guide App) designed to support access of first responders and essential workers to COVID-19 information and testing services. We also sought to better understand the COVID-19-related needs of these workers early in the pandemic.

METHODS

To understand overall community adoption, views and download data of the COVID-19 Guide App were described. To understand the adoption, appropriateness, and acceptability of the app and the unmet needs of workers, semistructured qualitative interviews were conducted by telephone, by video, and in person with first responders and essential workers in the San Francisco Bay Area who were recruited through purposive, convenience, and snowball sampling. Interview transcripts and field notes were qualitatively analyzed and presented using an implementation outcomes framework.

RESULTS

From its launch in April 2020 to September 2020, the app received 8262 views from unique devices and 6640 downloads (80.4% conversion rate, 0.61% adoption rate across the Bay Area). App acceptability was mixed among the 17 first responders interviewed and high among the 10 essential workers interviewed. Select themes included the need for personalized and accurate information, access to testing, and securing personal safety. First responders faced additional challenges related to interprofessional coordination and a "culture of heroism" that could both protect against and exacerbate health vulnerability.

CONCLUSIONS

First responders and essential workers both reported challenges related to obtaining accurate information, testing services, and other resources. A mobile app intervention has the potential to combat these challenges through the provision of disease-specific information and access to testing services but may be most effective if delivered as part of a larger ecosystem of support. Differentiated interventions that acknowledge and address the divergent needs between first responders and non-first responder essential workers may optimize acceptance and adoption.

摘要

背景

COVID-19 大流行给急救人员(如警察、消防和紧急医疗服务人员)和非医疗关键工作者(如食品、运输和其他行业的工人)带来了前所未有的挑战。鉴于其医疗专业知识,卫生系统可能非常适合支持这些工作人员,并且移动应用程序可以在保持社交距离要求的情况下覆盖当地社区。目前缺乏对基于实际移动应用程序的干预措施的正式评估。

目的

我们旨在评估一个学术医疗中心赞助的基于应用程序的干预措施(COVID-19 指南应用程序)的采用、可接受性和适当性,该应用程序旨在支持急救人员和关键工作者获取 COVID-19 信息和检测服务。我们还试图在大流行早期更好地了解这些工人的 COVID-19 相关需求。

方法

为了了解整体社区的采用情况,描述了 COVID-19 指南应用程序的观点和下载数据。为了了解应用程序的采用、适当性和可接受性以及工人的未满足需求,通过有目的、方便和滚雪球抽样,对在旧金山湾区的急救人员和关键工作者进行了电话、视频和面对面的半结构化定性访谈。使用实施结果框架对访谈记录和现场笔记进行定性分析和呈现。

结果

从 2020 年 4 月推出到 2020 年 9 月,该应用程序从独特的设备上获得了 8262 次查看和 6640 次下载(转化率为 80.4%,整个湾区的采用率为 0.61%)。接受度在接受采访的 17 名急救人员中参差不齐,在接受采访的 10 名关键工作者中较高。一些主题包括对个性化和准确信息、测试服务以及确保个人安全的需求。急救人员还面临与跨专业协调以及“英雄主义文化”相关的额外挑战,这些挑战既可以保护他们免受健康脆弱性的影响,也可能使其恶化。

结论

急救人员和关键工作者都报告了在获取准确信息、测试服务和其他资源方面面临的挑战。移动应用程序干预措施具有通过提供特定疾病的信息和获得测试服务来解决这些挑战的潜力,但如果作为更大支持生态系统的一部分提供,可能会更有效。区分急救人员和非急救关键工作者之间不同需求的差异化干预措施可能会优化接受度和采用率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b190/8139393/505f800dfd8c/jmir_v23i5e26573_fig1.jpg

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