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Related Experiment Video

Updated: Mar 13, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

Understanding and Promoting Effective Engagement With Digital Behavior Change Interventions.

Lucy Yardley¹, Bonnie J Spring², Heleen Riper³

¹Department of Psychology, University of Southampton, Southampton, United Kingdom.

American Journal of Preventive Medicine

|October 18, 2016

Summary

Focusing on "effective engagement" with digital behavior change interventions is key. This approach ensures sufficient user interaction to achieve desired health outcomes, rather than just measuring overall engagement.

Related Experiment Videos

Last Updated: Mar 13, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

Area of Science:

Digital Health
Behavioral Science
Human-Computer Interaction

Background:

Research on digital behavior change interventions (DBCIs) requires clear conceptualization and measurement of user engagement.
Current methods for assessing engagement need critical appraisal to align with intervention outcomes.

Purpose of the Study:

To critically review current approaches to conceptualizing and measuring engagement with DBCIs.
To discuss strategies for promoting effective engagement, including personalization and blended support.
To identify priority research areas for understanding and optimizing engagement in digital health.

Main Methods:

Expert consensus process to identify current research questions and guidance.
Critical reflection on existing conceptualizations and measurement techniques for engagement.
Discussion of tailoring strategies and integration of digital and human support.

Main Results:

Effective engagement, defined as sufficient interaction to achieve intended outcomes, is more valuable than simply measuring engagement levels.
There is a need for valid and efficient multidimensional models of engagement assessment.
User-centered, iterative design using mixed methods is crucial for developing effective DBCIs.

Conclusions:

Understanding the link between engagement and behavior change is paramount.
Future research should focus on developing and validating multidimensional engagement models.
Intervention design must be user-centered, iterative, and context-aware to maximize effectiveness.