Users Want Diverse, Multiple, and Personalized Behavior Change Support: Need-Finding Survey

Abstract

Behavior change research usually takes a theory-driven or application-specific approach. We took a user-centered view of real-world user needs and conducted a survey with 53 participants to investigate the overall behavior change goals and support preferences of everyday users. Our survey revealed three key themes. First, individual users have multiple behavior change goals, desired context types for behavior change reminders, and desired activities for self-tracking. Second, users have diverse and personalized desired actions, implementations, contexts, and reminders for their behavior change goals, as well as diverse preferences for behavior change support features and sensors. Third, users want to set custom personalized goals, reminder contexts, reminder messages, and even train custom machine learning models. Thus, users want multiple, diverse, and personalized behavior change support in the real world. We suggest a ‘convergence with connection and customization’ approach to meet the diverse, multiple, and personalized behavior change needs of everyday users.