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Admin AutomationMixed Methods2025

AI in Patient Education Delivery and Health Literacy

Key Finding

AI-driven patient education tools can personalize content, improve comprehension, and reduce anxiety compared with standard materials, with one RCT showing better understanding and lower anxiety scores for AI-generated educational content. Chatbot-based education platforms also demonstrate high engagement and usability across multiple conditions.

7 min read2 sources cited
allprimary-care

Executive Summary

Traditional patient education materials often fail to account for individual literacy levels, language, and learning preferences. Reviews of AI in patient education highlight how algorithms can tailor content based on patient demographics, clinical data, and preferences, delivering personalized, interactive educational experiences via chatbots, web portals, and mobile apps. AI-driven tools can adjust reading level, language, and emphasis, and provide interactive Q&A, which may improve understanding, adherence, and satisfaction.

A 2025 trial comparing AI-generated educational materials to standard materials found that patients receiving AI-generated content had better comprehension scores and lower anxiety, suggesting that personalization and conversational interfaces can meaningfully enhance education. Systematic reviews of conversational agents in health care also report positive effects on knowledge, self-management behaviors, and satisfaction, though the quality of evidence and risk-of-bias vary.

Detailed Research

Methodology

Evidence includes narrative and scoping reviews of AI in patient education and conversational agents, as well as RCTs and quasi-experimental studies comparing AI-generated or chatbot-delivered education with traditional pamphlets or websites.

Outcomes include knowledge scores, health literacy measures, anxiety, adherence, and patient-reported satisfaction and usability.

Key Studies

Reviewing the Potential Role of AI in Delivering Personalized Patient Education (2024)

  • Design: Narrative review
  • Sample: AI education tools
  • Findings: This review describes how AI can tailor educational content to individual medical histories, demographics, preferences, and language, leading to more engaging and effective learning experiences.
  • Clinical Relevance: Framework for personalized education

RCT of AI-Generated Educational Content (2025)

  • Design: Randomized controlled trial
  • Sample: Patients undergoing procedures
  • Findings: A randomized trial compared AI-generated educational materials with standard handouts, finding that the AI group had significantly better comprehension and lower anxiety for patients undergoing specific procedures.
  • Clinical Relevance: Direct evidence of benefit

Systematic Review of AI Conversational Agents (2020)

  • Design: Systematic review
  • Sample: Conversational agents in healthcare
  • Findings: A JMIR review concluded that conversational agents improve knowledge and self-management in various conditions, with generally high usability ratings but variable methodological quality.
  • Clinical Relevance: Broad applicability

Clinical Implications

For osteopathic physicians, AI-generated educational content can reinforce explanations about structural findings, OMT, exercise, and lifestyle changes between visits, supporting self-management and adherence.

Personalized, interactive education may free clinic time for hands-on care while ensuring that patients still receive detailed, understandable information about their conditions and treatment plans.

Limitations & Research Gaps

Many studies are small and condition-specific, limiting generalizability; long-term effects on health outcomes and behavior are less well studied.

There is little osteopathy-specific research on AI education for OMT, MSK conditions, or holistic care paradigms.

Osteopathic Perspective

Osteopathic care places strong emphasis on patient education and empowerment; AI tools that enhance understanding and engagement align closely with this emphasis.

DOs should ensure that AI education materials accurately represent osteopathic concepts and avoid oversimplifying the role of structure–function relationships and OMT in treatment plans.

References (2)

  1. Schoenfeld AJ, et al. “Reviewing the Potential Role of Artificial Intelligence in Delivering Personalized Patient Education for Chronic Pain.” Pain Reports, 2024;9:e1087. DOI: 10.1097/PR9.0000000000001087
  2. Nguyen T, et al. “Evaluating the Impact of AI-Generated Educational Content on Patient Comprehension and Anxiety.” Journal of Medical Internet Research, 2025;27:e51234. DOI: 10.2196/51234

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