Children’s self-report is essential for research, education, and healthcare, yet existing methods such as surveys and diaries can be experienced as tedious and so lead to disengagement and low-quality responses. Chatbots have been suggested as a way to support children through conversational interaction, using age-appropriate language and an empathetic tone. Here we explore what could be suitable conversational styles for such chatbots. Specifically, we explore rhyme as a child-centered conversational style. We first conducted a co-design workshop with 35 children, which revealed preferences for short, playful, and soothing conversational patterns. Building on these insights, we designed a voice-based sleep diary in rhyming style and compared it to a prose style in a within-subjects study involving 40 children aged 8-12. Results show that rhyming prompts significantly improved response quality across question types and age groups, while maintaining high engagement even among children who preferred the prose style. We contribute proof-of-concept empirical evidence and design insights demonstrating how phonological scaffolding exemplified through rhyme extends the design space of capability-adapted chatbots beyond semantic simplification alone. While limited to short-term, lab-based sessions, this work provides initial evidence that conversational style can function as a design lever.

Digital sleep diaries are widely used in clinical practice and research to monitor children’s subjective sleep quality. A well-known limitation of survey methods is that children may not provide high-quality responses because they cannot or are not motivated to do so. We examine how to design "live", continuous feedback in voice-based sleep diaries in order to enhance the quality of children’s responses. In a co-design workshop, we explored children’s preferences for different forms of feedback. We designed and compared experimentally symbolic (smiley), numeric, and no-feedback conditions, showing that both feedback types improved response quality across questions. Finally, an eight-day field study revealed that feedback resulted in higher and more consistent quality in self-report over time. Across these three studies, children valued playful and clear feedback, with preferences shifting depending on their cognitive needs. Our findings provide evidence that effective feedback must balance affective engagement and cognitive clarity and adapt to different contexts. We contribute empirically supported design insights for creating child-centered voice-based surveys that aim to enhance children’s adherence in independent self-report surveys. Our recommendations based on the study of sleep diaries can potentially be applied in other areas using voice-based surveys.

HCI technologies are increasingly used to promote the wellbeing of young people. While mental health professionals are significant resources to support young people in dealing with mental health challenges, little research has explored the distinctive perspectives between young people and professionals and how technology can be designed to navigate the tensions between them. To fill this gap, we conducted a two-stage study consisting of semi-structured interviews and a co-design workshop with university students and mental health professionals. Findings from the interviews revealed convergent and divergent perspectives between these two groups on the factors that motivate or discourage young people from seeking help from the professionals. In the workshop, insights of the interviews were further distilled into a set of card-based tools to facilitate shared understanding and collaboration between these two groups as they envisioned future technologies that address the interests and concerns of two groups. Our work contributes to ongoing discussions in HCI about how emerging technologies can be designed to promote shared understanding between these two groups and enable technology‑mediated mental healthcare tailored to individual needs and institutional contexts.