Eating disorder (ED) is a psychiatric condition that involves behaviors like binge and restrictive eating with severe health consequences, particularly prevalent among young women. While technology interventions exist, they typically focus on retrospective reflection or general management, missing the time window when an ED behavior is taking place. In this work, we conducted co-design sessions with 22 young women experiencing EDs to develop ideas for Just-in-Time (JIT) interventions, followed by interviews with five experts specialized in ED treatment. We found that eating plays varied roles in participants’ lives—from a means of gaining autonomy to automatic physiological responses—leading to design ideas including behavioral warnings, appetite management, food option redirection, psychological support systems, etc. By examining the characteristics of these designs with expert perspectives, we discuss what JIT support means for ED care and how to make it effective and sustainable. © 2026 Copyright held by the owner/author(s).

Amidst the increasingly prevalent smartphone addiction, we introduce StayFocused, a mobile app to help people focus on their tasks at hand by reducing compulsive smartphone use. Besides guiding people to set focus sessions for non-screen time, we incorporated reflective prompts probing individuals’ phone-checking intentions whenever they check their phones and a chatbot to deliver these prompts. To examine the effects of the reflective prompts and the chatbot support, we designed three versions of StayFocused: baseline, reflection, and reflection-chatbot, and conducted a stage-based between-subjects study with 36 college students over five weeks. We found that participants who received the reflective prompts were able to focus longer and resist distractions, and those with chatbot support seemed to better maintain their smartphone use reduction. By highlighting how participants reflected on their focus session activities and their preferences for the chatbot, we discuss the implications of designing persuasive conversational interfaces to reduce unintended behaviors.

Hand gestures are widely used in daily life for expressing emotions, yet gesture input is not part of existing emotion tracking systems. To seek a practical and effortless way of using gestures to inform emotions, we explore the relationships between gestural features and commonly experienced emotions by focusing on single-hand gestures that are easy to perform and capture. First, we collected 756 gestures (in photo and video pairs) from 63 participants who expressed different emotions in a survey, and then interviewed 11 of them to understand their gesture-forming rationales. We found that the valence and arousal level of the expressed emotions significantly correlated with participants’ finger-pointing direction and their gesture strength, and synthesized four channels through which participants externalized their expressions with gestures. Reflecting on the findings, we discuss how emotions can be characterized and contextualized with gestural cues and implications for designing multimodal emotion tracking systems and beyond.