Peer health posts surface new uncertainties, such as questions and concerns for readers. Prior work focused primarily on improving relevance and accuracy fails to address users' diverse information needs and emotions triggered. Instead, we propose directly addressing these by information augmentation. We introduce Evidotes, an information support system that augments individual posts with relevant scientific and anecdotal information retrieved using three user-selectable lenses (dive deeper, focus on positivity, and big picture). In a mixed-methods study with 17 chronic illness patients, Evidotes improved self-reported information satisfaction (3.2->4.6) and reduced self-reported emotional cost (3.4->1.9) compared to participants' baseline browsing. Moreover, by co-presenting sources, Evidotes unlocked information symbiosis: anecdotes made research accessible and contextual, while research helped filter and generalize peer stories. Our work enables an effective integration of scientific evidence and human anecdotes to help users better manage health uncertainty.
Physical inactivity remains a critical global health issue, yet scalable strategies for sustained motivation are scarce. Conversational agents designed as simulated exercising peers (SEPs) represent a promising alternative, but their long-term impact is unclear. We report a six-month randomized controlled trial (N=280) comparing individuals exercising alone, with a human peer, or with a large language model-driven SEP. Results revealed a partnership paradox: human peers evoked stronger social presence, while AI peers provided steadier encouragement and more reliable working alliances. Humans motivated through authentic comparison and accountability, whereas AI peers fostered consistent, low-stakes support. These complementary strengths suggest that AI agents should not mimic human authenticity but augment it with reliability. Our findings advance human-agent interaction research and point to hybrid designs where human presence and AI consistency jointly sustain physical activity.
Large language models (LLMs) offer novel opportunities to support health behavior change, yet existing work has narrowly focused on text-only interactions. Building on decades of HCI research on effective behavior change interactions, we present Bloom, an application for physical activity promotion that integrates an LLM-based health coaching chatbot with existing design strategies and UI elements. As part of Bloom's development, we conducted a redteaming evaluation and contribute a safety benchmark dataset. In a four-week randomized field study (N=54) comparing Bloom to a non-LLM control, we observed important shifts in psychological outcomes: participants in the LLM condition reported stronger beliefs that activity was beneficial, greater enjoyment, and more self-compassion. Both conditions significantly increased physical activity levels, doubling the proportion of participants meeting recommended weekly guidelines, though descriptively, we observed no advantage for the LLM condition in short-term physical activity levels. Instead, our findings suggest that LLMs may be more effective at shifting mindsets that precede longer-term behavior change.
Designing mobile, persuasive, and motivational interactions for sustainable behaviour change remains a challenge. Setting daily step goals on a mobile application can initially stimulate participation, but both the number of steps walked each day and the use of mobile applications decrease over time, even when individuals report high levels of motivation. To address this issue, we propose the integration of tailored gamification as a motivational mechanism, grounded in psychological theories. Self-Determination Theory is used to promote competence, while Regulatory Focus Theory is used to support individual differences and for tailoring motivational interactions. Gamification aims at reinforcing motivation and action-taking. In this article, we explain how we designed a motivational mobile application that incorporates these gamification mechanisms, and we describe how we evaluated its use during 28 days with 37 users. Results suggest a decrease in amotivation levels, and that promotion-focused individuals find gamified elements more motivational than prevention-focused ones.
Digital health coaches can deliver affordable, accessible behaviour coaching to broad populations. While prior research in motivational interviewing (MI) systems has emphasised emotional support strategies, it has overlooked the role of goal-setting behaviours in achieving successful coaching outcomes. We propose a coaching framework that provides motivational support for ambiguous clients while employing planning-focused strategies for action-ready clients. The user study evaluated our framework against a baseline system for promoting physical activity. Results showed significant increases in users' readiness to change after interacting with our motivational coaching chatbots. Participants perceived our agent as more adherent to MI principles and more effective at planning than the baseline. Qualitative analysis revealed that users who agreed with the agent on a change plan experienced the greatest increases in intrinsic motivation. Finally, we examine how these findings align with expert opinions that informed our system design principles and discuss implications for LLM-based health coaching.
Physical activity trackers rely on fixed daily step goals, treating the day as the primary unit for planning and evaluating activity. However, these goals often misalign with everyday life: schedules fluctuate, opportunities for movement vary, and long-term targets can be difficult to sustain, leading to frustration and disengagement. Despite growing evidence that short bouts of movement can meaningfully improve health, current systems provide limited support for acting on these brief, situated opportunities. This paper investigates micro-goals (i.e., brief, situated goals) as an alternative framing for supporting physical activity. We developed Mikro, a smartwatch app enabling on-the-go micro-goal setting, and deployed it in a 27-day field study with 16 participants. Our findings show that micro-goals encouraged frequent tailoring, supported immediate action, and helped participants capitalize on small opportunities for movement. We argue that micro-goals can complement daily step targets by scaffolding more flexible, adaptive, and engaging ways of staying active.
In traditional journaling practices, authors express and process their thoughts by writing them down. We propose a somaesthetic-inspired alternative that uses the human body, rather than written words, as the medium of expression. We coin this embodied journaling, as people's isolated body movements and spoken words become the canvas of reflection. We implemented embodied journaling in virtual reality and conducted a within-subject user study (n=20) to explore the emergent behaviours from the process, comparing its expressive and reflective qualities to those of written journaling. When writing-based norms and affordances were absent, we found that participants defaulted towards unfiltered emotional expression, often forgoing words altogether. Rather, subconscious body motion and paralinguistic acoustic qualities unveiled deeper, sometimes hidden feelings, prompting reflection that happens after emotional expression rather than during it. We discuss both the capabilities and pitfalls of embodied journaling, ultimately challenging the idea that reflection culminates in linguistic reasoning.