Parenting Journal · Volume 2 · Issue 5 · Licensed source edition
Technology matters: AI‐driven tools in children's mental healthcare: perspectives from young people and parents
Originally published 2025-11-12 · Child and Adolescent Mental Health
Wiley · DOI 10.1111/camh.70045 ↗
AI / system type
Proposed speech/NLP predictive AI; speculative-story consultation
Direct parenting evidenceDirectly addresses parents or caregiving, including parent studies, syntheses and audits of parenting advice.
The AI connection
The proposed narrow AI analyzes expressed emotion in a parent’s five-minute speech sample to inform child mental-health assessment.
Why this reading matters
Brings children’s and parents’ voices into the early design of tools that could otherwise label families without their input.
Editorial reading guide · Respect
Would our child’s future opportunities be shaped by an AI interpretation of my speech?
Participants questioned data access, future reuse, neurodivergent communication bias, and unequal access to care. The stories helped families examine consequences of risk prediction beyond its proposed technical accuracy.
Study context
Twelve young people and six parents discussed fictional futures of an AI tool intended to analyze parents’ speech about their children.
Age / stage: Young people aged 13–18 years, plus parents of autistic children
Read with three questions
- What did young people want to know about data access and retention?
- Why might a speech model misinterpret neurodivergent parents?
- How did participants distinguish useful care from potentially harmful future risk labels?
Keep the limits in view
This is a small engagement report about imagined applications, not a trial or formal estimate of population attitudes. The workshops did not validate the speech model or show whether predicted risk improves child mental-health care.
The text below is the original article’s licensed repository edition. Its wording is not rewritten. Use the Paper Agent beside the text to locate evidence; open the source for figures, tables and complete context.
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Follow the original.
Original authorship, publication date, journal and DOI are preserved. This issue’s TRICK placement and reading questions are editorial additions, not claims made by the original authors.
Zoë Firth; Christine Aicardi; Stephen Oram; Nicholas Cummins; Alice Wickersham; Helen L Fisher; Johnny Downs (2025). Technology matters: AI‐driven tools in children's mental healthcare: perspectives from young people and parents Child and Adolescent Mental Health. https://doi.org/10.1111/camh.70045
Permissions checked against the saved article notice; repository publication notices screened 2026-11-04. This is not a new peer-review decision. The source authors and publishers are not represented as endorsing this issue.