If you design health behavior change interventions, you’ve probably heard of behavioral economics. Concepts from behavioral economics—often called “nudges”—can inform incentive design, participation strategies, and the feature sets of interventions with the goal of impacting behavior to achieve positive outcomes.
However, many behavioral economic-inspired features don’t achieve their desired goals. Reasons why not include:
*Not all practitioners share an evidence-based understanding of how behavioral economics works, and therefore may misapply concepts;
*Users are more responsive to different behavioral economics concepts at different points in the behavior change experience, so an experience map must be layered into the design process;
*And individual differences also influence which behavioral economics concepts most affect behavior, so a deep understanding of the user is required.
In this talk, we’ll review several of the core concepts in behavioral economics. We’ll share examples of how they can be misapplied in digital design and explain why they are not effective in those contexts.
But don’t fret; we’ll also share best practices for applying these concepts based on the evidence-based literature. We’ll dive into how human-centered design—understanding the user’s needs and context—can save the day. We consider the user’s experience with an intervention over time and identify critical milestones and touchpoints. At each stage, the user’s needs change, and as a result, the particular behavioral economics principles that most effectively influence behavior do too. We’ll add nuance by considering the different “flavors” of features that can be used depending on the user’s psychological and environmental status.
*Strategies for evaluating longitudinal user needs in health interventions
*Options for better understanding a user’s psychographic profile
*Tactics to select the most effective behavioral economics technique(s) to effect change for specific users at specific timepoints
*Best practices to translate concepts to intervention features
Presented at UXPA Boston, May 19, 2007.