Aljoscha Rimpler, Björn S. Siepe, Carlotta L. Rieble, Ricarda K. K. Proppert, Eiko I. Fried
{"title":"Introducing FRED: Software for Generating Feedback Reports for Ecological Momentary Assessment Data","authors":"Aljoscha Rimpler, Björn S. Siepe, Carlotta L. Rieble, Ricarda K. K. Proppert, Eiko I. Fried","doi":"10.1007/s10488-023-01324-4","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":7195,"journal":{"name":"Administration and Policy in Mental Health and Mental Health Services Research","volume":"51 4","pages":"490 - 500"},"PeriodicalIF":2.0000,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11196357/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Administration and Policy in Mental Health and Mental Health Services Research","FirstCategoryId":"3","ListUrlMain":"https://link.springer.com/article/10.1007/s10488-023-01324-4","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
The aim of Administration and Policy in Mental Health and Mental Health Services is to improve mental health services through research. This journal primarily publishes peer-reviewed, original empirical research articles. The journal also welcomes systematic reviews. Please contact the editor if you have suggestions for special issues or sections focusing on important contemporary issues. The journal usually does not publish articles on drug or alcohol addiction unless it focuses on persons who are dually diagnosed. Manuscripts on children and adults are equally welcome. Topics for articles may include, but need not be limited to, effectiveness of services, measure development, economics of mental health services, managed mental health care, implementation of services, staffing, leadership, organizational relations and policy, and the like. Please review previously published articles for fit with our journal before submitting your manuscript.