Parenting Journal · Volume 2 · Issue 5 · Licensed source edition
Assessing AI-Generated Autism Information for Healthcare Use: A Cross-Linguistic and Cross-Geographic Evaluation of ChatGPT, Gemini, and Copilot
Originally published 2025-10-30 · Healthcare
Multidisciplinary Digital Publishing Institute (MDPI) · DOI 10.3390/healthcare13212758 ↗
AI / system type
Generative AI/LLM multilingual answer benchmark
Family implicationsDesign, ethics, stakeholder or technical evidence with child/family implications; household benefits are not assumed.
The AI connection
ChatGPT, Gemini, and Copilot answered caregiver autism questions under controlled language and location conditions.
Why this reading matters
Adds linguistic context to family fact-checking rather than treating English-language benchmark performance as universal.
Editorial reading guide · Trust
Is an AI answer equally reliable in the language our family actually uses?
Accuracy, references, actionability, and readability did not point to one uniformly best tool. Turkish and English outputs differed, and medicalized framing remained common, showing that trust depends on language and the kind of help sought.
Study context
Researchers evaluated answers to 44 caregiver-focused autism questions in English and Turkish across the USA, England, and Türkiye.
Age / stage: Autism information for families of children roughly 2–18 years; no family users enrolled
Read with three questions
- How did accuracy trade off against references or actionable support?
- Which language differences matter for your family’s questions?
- How might medicalized framing shape a parent’s view of an autistic child?
Keep the limits in view
Only three systems, two languages, and single-turn prompts were tested in May 2025. Content scores cannot show whether families understood or acted on the advice, and should not be generalized to all cultures or later model versions.
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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.
Salih Rakap; Emrah Gulboy; Uygar Bayrakdar; Goksel Cure; Busra Besdere; Burak Aydin (2025). Assessing AI-Generated Autism Information for Healthcare Use: A Cross-Linguistic and Cross-Geographic Evaluation of ChatGPT, Gemini, and Copilot Healthcare. https://doi.org/10.3390/healthcare13212758
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.