介绍 FRED:为生态瞬间评估数据生成反馈报告的软件。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-01-10 DOI:10.1007/s10488-023-01324-4
Aljoscha Rimpler, Björn S. Siepe, Carlotta L. Rieble, Ricarda K. K. Proppert, Eiko I. Fried
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引用次数: 0

摘要

生态瞬间评估(EMA)是一种利用智能手机应用程序或可穿戴设备收集日常生活信息的数据收集方法。与传统调查相比,EMA 具有提高生态有效性等优点。然而,特别是长时间的数据收集可能会干扰参与者的日常活动,给他们造成负担。因此,EMA 研究的数据缺失率相对较高,并面临合规性问题。让参与者通过可访问的反馈报告来获取他们的数据,就像在公民科学活动中看到的那样,可能会提高参与者的积极性。生成此类报告的现有框架主要针对临床环境中的单个个体,不能很好地扩展到大型数据集。在此,我们引入了 FRED(EMA 数据反馈报告),以应对为众多参与者提供个性化报告的挑战。FRED 是一个交互式在线工具,参与者可以在其中探索自己的个性化数据报告。我们使用 WARN-D 研究的数据展示了 FRED,该研究连续 85 天对 867 名参与者进行了四次每日调查和一次每周调查,每位参与者最多可获得 352 个观察结果。FRED 包括描述性统计、时间序列可视化和选定 EMA 变量的网络分析。参与者可以通过 R 编程语言开发的 Shiny 应用程序在线访问报告。我们提供 FRED 的代码和基础架构,希望它对研究和临床环境都有用,因为它可以灵活地适应其他项目的需要,从而实现生成个性化数据报告的目标。
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Introducing FRED: Software for Generating Feedback Reports for Ecological Momentary Assessment Data

Ecological Momentary Assessment (EMA) is a data collection approach utilizing smartphone applications or wearable devices to gather insights into daily life. EMA has advantages over traditional surveys, such as increasing ecological validity. However, especially prolonged data collection can burden participants by disrupting their everyday activities. Consequently, EMA studies can have comparably high rates of missing data and face problems of compliance. Giving participants access to their data via accessible feedback reports, as seen in citizen science initiatives, may increase participant motivation. Existing frameworks to generate such reports focus on single individuals in clinical settings and do not scale well to large datasets. Here, we introduce FRED (Feedback Reports on EMA Data) to tackle the challenge of providing personalized reports to many participants. FRED is an interactive online tool in which participants can explore their own personalized data reports. We showcase FRED using data from the WARN-D study, where 867 participants were queried for 85 consecutive days with four daily and one weekly survey, resulting in up to 352 observations per participant. FRED includes descriptive statistics, time-series visualizations, and network analyses on selected EMA variables. Participants can access the reports online as part of a Shiny app, developed via the R programming language. We make the code and infrastructure of FRED available in the hope that it will be useful for both research and clinical settings, given that it can be flexibly adapted to the needs of other projects with the goal of generating personalized data reports.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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