Artificial intelligence in pain: A comprehensive review

February 3, 2026

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Key Points

This review aims to evaluate the responses generated by AI chatbots concerning pain in terms of readability, quality, trustworthiness, and adherence to clinical guidelines.
Comprehensive analysis of studies published between 2024 and 2025 evaluating AI chatbots' responses to pain-related queries.
Utilized readability indices like Flesch Reading Ease and Flesch-Kincaid Grade Level, along with quality measures such as DISCERN and JAMA criteria.
Compared chatbot responses against national and international clinical guidelines.
AI models generally provided accurate basic information about pain.
Most responses exceeded recommended readability levels for patient education materials.
Quality and trustworthiness were often rated as moderate, with notable gaps in discussing treatment risks and transparency of sources.

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Comprehensive review assesses AI chatbot responses about pain, highlighting challenges in quality and guidelines compliance.

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Özbek et al. (2026) studied this question.

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