001     1022017
005     20240226075420.0
024 7 _ |a 10.2196/preprints.51689
|2 doi
024 7 _ |a 10.34734/FZJ-2024-01154
|2 datacite_doi
037 _ _ |a FZJ-2024-01154
041 _ _ |a English
100 1 _ |a Sahandi Far, Mehran
|0 P:(DE-Juel1)177922
|b 0
|e Corresponding author
245 _ _ |a JTrack-EMA+: A Cross-platform Ecological Momentary Assessment Application (Preprint)
260 _ _ |c 2023
336 7 _ |a Preprint
|b preprint
|m preprint
|0 PUB:(DE-HGF)25
|s 1706689146_5585
|2 PUB:(DE-HGF)
336 7 _ |a WORKING_PAPER
|2 ORCID
336 7 _ |a Electronic Article
|0 28
|2 EndNote
336 7 _ |a preprint
|2 DRIVER
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a Output Types/Working Paper
|2 DataCite
520 _ _ |a Traditional in-clinic methods of collecting self-reported information are costly, time-consuming, subjective, and often limited in the quality and quantity of observation. However, smartphone-based Ecological Momentary Assessments (EMA) provide complementary information to in-clinic visits by collecting real-time, frequent, and longitudinal data that are ecologically valid. While these methods are promising, they are often prone to various technical obstacles. Yet the availability and interoperability with different operating systems (OSs) need to be fully resolved in existing solutions. This shortness increases the selection bias, development and maintenance costs, and time. It also limits the configurability and adoption of existing solutions to new problems.The primary aim of this research was to develop a cross-platform EMA application that ensures a uniform user experience and core features across various OSs. Emphasis was placed on minimizing the resources and expenses associated with the development and maintenance and maximizing the integration and adaptability in various clinical trials, all while maintaining strict adherence to security and privacy protocols. JTrack EMA+ was designed and implemented in accordance with the FAIR principles (findable, accessible, interpretable, and reusable) in both its architecture and data management layers, thereby reducing the burden of integration for clinicians and researchers."JTrack-EMA+" is built using the Flutter framework, enabling it to run seamlessly across different platforms. This platform comprises two main components. JDash is an online management tool created using Python with the Django framework. This online dashboard offers comprehensive study management tools, including assessment design, user administration, data quality control, and a reminder casting center. And JTrack-EMA+ application supports a wide range of question types, allowing flexibility in assessment design. It also has configurable assessment logic and the ability to include supplementary materials for a richer user experience. It strongly commits to security and privacy and complies with the General Data Protection Regulations (GDPR) to safeguard user data and ensure confidentiality.We investigated our platform in a pilot study with 480 days of follow-up to assess participants' compliance. The six-month average compliance was 49.34%, significantly declining (P<0.05) from 66.75% in the first month to 42.0% in the sixth month. These results show the potential of using our newly introduced platform in remote and at-home-based EMA assessments.JTrack EMA+ platform is a pioneer in prioritizing platform-independent architecture that provides an easy entry point for clinical researchers to deploy EMA in their respective clinical studies. Remote and home-based assessments of EMA using this platform can provide valuable insights into patients' daily lives, particularly in a population with limited mobility or inconsistent access to healthcare services.
536 _ _ |a 5254 - Neuroscientific Data Analytics and AI (POF4-525)
|0 G:(DE-HGF)POF4-5254
|c POF4-525
|f POF IV
|x 0
536 _ _ |a 5251 - Multilevel Brain Organization and Variability (POF4-525)
|0 G:(DE-HGF)POF4-5251
|c POF4-525
|f POF IV
|x 1
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Fischer, Jona Marcus
|0 P:(DE-Juel1)173663
|b 1
700 1 _ |a Senge, Svea
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Rathmakers, Robin
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Meissner, Thomas
|0 P:(DE-HGF)0
|b 4
700 1 _ |a Schneble, Dominik
|0 P:(DE-HGF)0
|b 5
700 1 _ |a Narava, Mamaka
|0 P:(DE-Juel1)190196
|b 6
700 1 _ |a Eickhoff, Simon
|0 P:(DE-Juel1)131678
|b 7
700 1 _ |a Dukart, Jürgen
|0 P:(DE-Juel1)177727
|b 8
773 _ _ |a 10.2196/preprints.51689
856 4 _ |y OpenAccess
|z StatID:(DE-HGF)0510
|u https://juser.fz-juelich.de/record/1022017/files/Preprint_Fulltext.pdf
856 4 _ |y OpenAccess
|x icon
|z StatID:(DE-HGF)0510
|u https://juser.fz-juelich.de/record/1022017/files/Preprint_Fulltext.gif?subformat=icon
856 4 _ |y OpenAccess
|x icon-1440
|z StatID:(DE-HGF)0510
|u https://juser.fz-juelich.de/record/1022017/files/Preprint_Fulltext.jpg?subformat=icon-1440
856 4 _ |y OpenAccess
|x icon-180
|z StatID:(DE-HGF)0510
|u https://juser.fz-juelich.de/record/1022017/files/Preprint_Fulltext.jpg?subformat=icon-180
856 4 _ |y OpenAccess
|x icon-640
|z StatID:(DE-HGF)0510
|u https://juser.fz-juelich.de/record/1022017/files/Preprint_Fulltext.jpg?subformat=icon-640
909 C O |o oai:juser.fz-juelich.de:1022017
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)177922
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)173663
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 6
|6 P:(DE-Juel1)190196
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 7
|6 P:(DE-Juel1)131678
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 8
|6 P:(DE-Juel1)177727
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|0 G:(DE-HGF)POF4-525
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Decoding Brain Organization and Dysfunction
|9 G:(DE-HGF)POF4-5254
|x 0
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|0 G:(DE-HGF)POF4-525
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Decoding Brain Organization and Dysfunction
|9 G:(DE-HGF)POF4-5251
|x 1
914 1 _ |y 2023
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)INM-7-20090406
|k INM-7
|l Gehirn & Verhalten
|x 0
980 _ _ |a preprint
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)INM-7-20090406
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21