Evidence map›Paper›PMID 39874571›Full record

ArticleJournal of medical Internet research2025

Cross-Platform Ecological Momentary Assessment App (JTrack-EMA+): Development and Usability Study.

Mehran Sahandi Far, Jona M Fischer, Svea Senge, Robin Rathmakers, Thomas Meissner, Dominik Schneble, Mamaka Narava, Simon B Eickhoff, Juergen Dukart

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Mehran Sahandi FarResearch Centre Jülich, Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Jülich, Germany.ORCID 0000-0002-5311-8286
Jona M FischerResearch Centre Jülich, Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Jülich, Germany.ORCID 0000-0003-3011-4968
Svea SengeDepartment of General Paediatrics, Neonatology and Paediatric Cardiology, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany.ORCID 0009-0008-6378-2165
Robin RathmakersDepartment of General Paediatrics, Neonatology and Paediatric Cardiology, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany.ORCID 0009-0000-4120-4825
Thomas MeissnerDepartment of General Paediatrics, Neonatology and Paediatric Cardiology, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany.ORCID 0000-0003-3091-5546
Dominik SchnebleDepartment of General Paediatrics, Neonatology and Paediatric Cardiology, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany.ORCID 0009-0005-0888-6920
Mamaka NaravaResearch Centre Jülich, Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Jülich, Germany.ORCID 0009-0007-6003-1676
Simon B EickhoffResearch Centre Jülich, Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Jülich, Germany.ORCID 0000-0001-6363-2759
Juergen DukartResearch Centre Jülich, Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Jülich, Germany.ORCID 0000-0003-0492-5644

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTraditional 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 (EMAs) 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. However, despite the potential of smartphone-based EMAs, they face technical obstacles that impact adaptability, availability, and interoperability across devices and operating systems. Deficiencies in these areas can contribute to selection bias by excluding participants with unsupported devices or limited digital literacy, increase development and maintenance costs, and extend deployment timelines. Moreover, these limitations not only impede the configurability of existing solutions but also hinder their adoption for addressing diverse clinical challenges.

objectiveThe primary aim of this research was to develop a cross-platform EMA app that ensures a uniform user experience and core features across various operating systems. Emphasis was placed on maximizing the integration and adaptability to various study designs, all while maintaining strict adherence to security and privacy protocols. JTrack-EMA+ was designed and implemented per the FAIR (findable, accessible, interpretable, and reusable) principles in both its architecture and data management layers, thereby reducing the burden of integration for clinicians and researchers.

methodsJTrack-EMA+ was built using the Flutter framework, enabling it to run seamlessly across different platforms. This platform comprises two main components. JDash (Research Centre Jülich, Institute of Neuroscience and Medicine, Brain and Behaviour [INM-7]) is an online management tool created using Python (Python Software Foundation) with the Django (Django Software Foundation) framework. This online dashboard offers comprehensive study management tools, including assessment design, user administration, data quality control, and a reminder casting center. The JTrack-EMA+ app 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 to safeguard user data and ensure confidentiality.

resultsWe investigated our platform in a pilot study with 480 days of follow-up to assess participants' compliance. The 6-month average compliance was 49.3%, significantly declining (P=.004) from 66.7% in the first month to 42% in the sixth month.

conclusionsThe JTrack-EMA+ platform prioritizes platform-independent architecture, providing 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 health care services.

Indexed as

Clinical Studies as TopicMobile ApplicationsPatient ComplianceSelf ReportSoftwareAdultHumansInfant, NewbornParentsPilot Projectsapplicationbiomarkercostlydata managementdigital biomarkersecological momentary assessmentmobile healthmobile phonemobilitymonitoringremote monitoringsmartphoneuser experience

Identifiers

PMID39874571
PMCPMC11815298

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.