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An iterative, interdisciplinary, collaborative framework for developing and evaluating digital behavior change

Madalina Sucala¹, Nnamdi Peter Ezeanochie¹, Heather Cole-Lewis¹

¹Johnson and Johnson Health and Wellness Solutions Inc., New Brunswick, NJ, USA.

Translational Behavioral Medicine

|July 23, 2019

Summary

This summary is machine-generated.

Technology can improve health behaviors, but challenges remain in creating engaging, personalized digital interventions. This framework integrates behavior science, design, and data science for effective development and evaluation of digital behavior change interventions (DBCIs).

Keywords:

Digital behavior change interventions Evaluation methods Intervention development Intervention optimization Intervention personalization

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Area of Science:

Behavioral Science
Human-Centered Design
Data Science
Digital Health

Background:

Technology offers transformative potential for health behavior monitoring and improvement.
Current challenges include creating engaging, scientifically sound, and personalized interventions.
Existing models for intervention and product development require integration with behavior science principles.

Purpose of the Study:

To present a framework for developing and evaluating digital behavior change interventions (DBCIs).
To leverage expertise from behavior science, human-centered design, and data science.
To address challenges in intervention engagement, evaluation, and personalization.

Main Methods:

Reviewed current models for intervention development and evaluation.
Incorporated technology industry models for product development.
Proposed an iterative framework with accelerated testing cycles.

Main Results:

A comprehensive framework detailing phases from development to evaluation.
Identification of optimal practices, stakeholders, and evaluation methods for DBCIs.
Emphasis on an iterative process to maximize intervention outcomes.

Conclusions:

The proposed framework guides the development of effective digital behavior change interventions (DBCIs).
Highlights the need for collaboration between academia and industry.
Promotes the creation of DBCIs that are both effective and reach diverse populations.