ULTEMAT: A mobile framework for smart ecological momentary assessments and interventions

Area of Science:

• Digital Health
• Mobile Health Interventions
• Psychological Assessment

Background:

• Ecological Momentary Assessments (EMAs) are crucial for real-time data collection in mental health.
• Current mobile health interventions can be improved by more contextually relevant assessment delivery.
• The H2020 E-COMPARED project sought to enhance mental health support through mobile technology.

Purpose of the Study:

• Introduce ULTEMAT, a novel Android library for delivering EMAs on mobile devices.
• Explore the utility of context-aware (event-based) triggers for EMA delivery.
• Demonstrate the application of ULTEMAT within the MoodBuster app.

Main Methods:

• Development of the ULTEMAT Android library.
• Implementation of context-aware triggers for scheduling EMAs.
• Utilizing ULTEMAT in the MoodBuster application for mental health assessment.

Main Results:

• ULTEMAT facilitates the scheduling of EMAs using context-aware triggers.
• The library's design supports timely and appropriate delivery of assessments.
• A similar approach can be extended to Ecological Momentary Interventions (EMIs).

Conclusions:

• Context-aware triggers enhance the effectiveness of mobile mental health interventions.
• ULTEMAT provides a robust framework for context-aware EMA delivery.
• Mobile health technologies like ULTEMAT show promise for improving mental healthcare accessibility and efficacy.