When motivation can be more than a message: designing agents to boost physical activity

2025-08-17

AI Summary

Virtual fitness agents have long been confined to a “coach” role, lacking deep social connection and limiting user engagement. Method: Through semi-structured interviews with 12 users and thematic analysis—grounded in human–computer interaction and behavioral science theories—we identified a critical tension in social comparison: users require both *effort visibility* and *performance authenticity* from agents. Overly optimized or ambiguous activity representations eroded trust and motivation, whereas agents modeled on realistic human baselines and explicitly conveying effort fostered greater trust and sustained participation. Contribution/Results: We propose the *Co-Embodied Effort* design framework, comprising three interrelated components—behavioral cues, narrative anchoring, and personalized performance representation—to support socially resonant, credible, and motivationally effective virtual fitness agents. This framework advances theoretical understanding and offers actionable design guidelines for next-generation embodied agents in health behavior support.

Technology Category

• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Multiagent Systems: Agent-Based Simulation and Emergent Behavior

Application Category

• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Virtual agents are commonly used in physical activity interventions to support behavior change, often taking the role of coaches that deliver encouragement and feedback. While effective for compliance, this role typically lacks relational depth. This pilot study explores how such agents might be perceived not just as instructors, but as co-participants: entities that appear to exert effort alongside users. Drawing on thematic analysis of semi-structured interviews with 12 participants from a prior physical activity intervention, we examine how users interpret and evaluate agent effort in social comparison contexts. Our findings reveal a recurring tension between perceived performance and authenticity. Participants valued social features when they believed others were genuinely trying. In contrast, ambiguous or implausible activity levels undermined trust and motivation. Many participants expressed skepticism toward virtual agents unless their actions reflected visible effort or were grounded in relatable human benchmarks. Based on these insights, we propose early design directions for fostering co-experienced exertion in agents, including behavioral cues, narrative grounding, and personalized performance. These insights contribute to the design of more engaging, socially resonant agents capable of supporting co-experienced physical activity.

Problem

• Exploring virtual agents as co-participants in physical activity
• Examining user perceptions of agent effort and authenticity
• Designing agents with visible effort to enhance trust and motivation

Innovation

• Agents as co-participants in physical activity
• Behavioral cues to show agent effort
• Personalized performance for social resonance