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TRUVACE RECORD VERSION record: TRV-2026-0127 version: 1 kind: certified reason: Certified into the record timestamp: 2026-07-13T08:29:45.836403Z status: published lens: g_space sector: health headline: Young people’s perceptions and recommendations for conversational generative artificial intelligence in youth mental health dek: Conversational generative artificial intelligence agents (or genAI chatbots) could benefit youth mental health, yet young people's perspectives remain underexplored. We examined the Mental health Intelligence Agent (Mia), a genAI chatbot originally designed for professionals in Australian youth services. Following co-design, 32 young people participated in online workshops exploring their perceptions of genAI chatbots in youth mental health and to develop recommendations for reconceptualising Mia for consumers a… gain_title: Co-design workshops with 32 young people generated system requirements for reconceptualising the professional-focused Mia genAI chatbot for young consumers and integrating it into Australian youth services, with potential to benefit youth mental health. problem_title: (none) trace_subject: (none) gain_reading: Co-design workshops with 32 young people generated system requirements for reconceptualising the professional-focused Mia genAI chatbot for young consumers and integrating it into Australian youth services, with potential to benefit youth mental health. gain_evidence: could benefit youth mental health | to develop recommendations for reconceptualising Mia for consumers and integrating it into services problem_reading: (none) problem_evidence: (none) quick_read: On 2026-06-19, a peer-reviewed study reported online workshops with 32 young people to examine the Mental health Intelligence Agent Mia, a genAI chatbot originally designed for professionals in Australian youth services. Following co-design, participants explored perceptions of genAI chatbots in youth mental health and developed recommendations for reconceptualising Mia for consumers and integrating it into services, with four themes identified through reflexive thematic analysis. The work matters because it translates youth perspectives into concrete system requirements for service integration, addressing a gap where young people's perspectives remain underexplored despite claims that chatbots could benefit youth mental health. What remains uncertain is whether the proposed requirements actually improve outcomes or mitigate risks like dehumanising care, as the source reports perceptions and recommendations rather than measured clinical effects by the publication date. limitation: Findings are bounded by a small co-design sample and a specific service context, as the work involved 32 young people and a chatbot originally designed for professionals in Australian youth services, so transferability to other populations and systems remains uncertain. tag: Evidence-backed gain key_points: 32 young people participated in online workshops after co-design to explore perceptions of genAI chatbots | Study examined Mia, a genAI chatbot originally designed for professionals in Australian youth services | Analysis used reflexive thematic analysis and produced four themes including Right tool, right place, right time? rundown: The project centered on Mia, described as the Mental health Intelligence Agent, a genAI chatbot originally designed for professionals in Australian youth services. After initial co-design, the team ran online workshops with 32 young people to explore perceptions and to develop recommendations for reconceptualising Mia for consumers. Reflexive thematic analysis produced four themes: Humanising AI without dehumanising care, I need to know what's under the hood, Right tool, right place, right time?, and Making it mine on safe ground. The authors state the work informs ethics, design, development, implementation, and governance of genAI chatbots in youth mental health contexts. sources: - peer_reviewed | npj Digital Medicine | https://doi.org/10.1038/s41746-026-02888-9 | 2026-06-19 prev: 0000000000000000000000000000000000000000000000000000000000000000
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