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Investigating the Quality of Chat Generative Pretrained Transformer's (ChatGPT) Parenting Advice
Tiffany Munzer1, Phoebe Jordan2, Julie Sturza1
1Department of Pediatrics, University of Michigan, Ann Arbor, MI.
Summary
This study evaluated Chat Generative Pretrained Transformer (ChatGPT) parenting advice, finding overall accuracy but variable quality across topics. Screen media advice was notably lower quality than mental health or smoking/vaping guidance.
Area of Science:
- Artificial Intelligence in Healthcare
- Parenting Research
- Digital Health
Background:
- Chat Generative Pretrained Transformer (ChatGPT) offers accessible parenting guidance.
- The quality of AI-generated parenting advice requires thorough examination.
Purpose of the Study:
- To assess the quality of parenting advice provided by ChatGPT.
- To identify variations in advice quality across different parental concern topics.
Main Methods:
- 100 clinically relevant ChatGPT queries were developed based on parental concerns.
- ChatGPT 4o responses were evaluated using an adapted coding scheme for advice quality.
- ANOVA and post hoc analyses compared advice quality across topics like screen media, mental health, and feeding.
Main Results:
- ChatGPT provided accurate information on parenting benefits but often omitted risks and psychosocial nuances.
- Advice quality varied significantly by topic (p = 0.003).
- Screen media advice (mean=3.7) was lower quality compared to mental health (mean=4.6) and smoking/vaping (mean=5.0) advice.
Conclusions:
- ChatGPT's parenting advice is generally accurate but inconsistent in quality across different subjects.
- Topics like screen media may require more nuanced advice than ChatGPT currently provides.
- Further research is needed to ensure AI parenting tools offer comprehensive and context-aware guidance.
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