Comparing patient education tools for chronic pain medications: Artificial intelligence chatbot versus traditional patient information leaflets

Comparing patient education tools for chronic pain medications: Artificial intelligence chatbot versus traditional patient information leaflets

Artificial intelligence (AI) chatbots like Conversational Generative Pre-trained Transformer (ChatGPT) have recently created much buzz, especially regarding patient education. Such informed patients understand and adhere to the management and get involved in shared decision making. The accuracy and...

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Bibliographic Details
Published in:Indian journal of anaesthesia Vol. 68; no. 7; pp. 631 - 636
Main Authors: Gondode, Prakash, Duggal, Sakshi, Garg, Neha, Sethupathy, Surrender, Asai, Omshubham, Lohakare, Pooja
Format: Journal Article
Language:English
Published: India Medknow Publications & Media Pvt. Ltd 01-07-2024
Wolters Kluwer - Medknow
Wolters Kluwer Medknow Publications
Subjects:
Accuracy
analgesia
Artificial intelligence
Chatbots
chatgpt
Chronic pain
Clinical decision making
medication adherence
Original
Patient education
Readability
chronic pain
readability
ChatGPT
patient education
analgesia
AI
medication adherence
artificial intelligence
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Summary:Artificial intelligence (AI) chatbots like Conversational Generative Pre-trained Transformer (ChatGPT) have recently created much buzz, especially regarding patient education. Such informed patients understand and adhere to the management and get involved in shared decision making. The accuracy and understandability of the generated educational material are prime concerns. Thus, we compared ChatGPT with traditional patient information leaflets (PILs) about chronic pain medications. Patients' frequently asked questions were generated from PILs available on the official websites of the British Pain Society (BPS) and the Faculty of Pain Medicine. Eight blinded annexures were prepared for evaluation, consisting of traditional PILs from the BPS and AI-generated patient information materials structured similar to PILs by ChatGPT. The authors performed a comparative analysis to assess materials' readability, emotional tone, accuracy, actionability, and understandability. Readability was measured using Flesch Reading Ease (FRE), Gunning Fog Index (GFI), and Flesch-Kincaid Grade Level (FKGL). Sentiment analysis determined emotional tone. An expert panel evaluated accuracy and completeness. Actionability and understandability were assessed with the Patient Education Materials Assessment Tool. Traditional PILs generally exhibited higher readability ( values < 0.05), with [mean (standard deviation)] FRE [62.25 (1.6) versus 48 (3.7)], GFI [11.85 (0.9) versus 13.65 (0.7)], and FKGL [8.33 (0.5) versus 10.23 (0.5)] but varied emotional tones, often negative, compared to more positive sentiments in ChatGPT-generated texts. Accuracy and completeness did not significantly differ between the two. Actionability and understandability scores were comparable. While AI chatbots offer efficient information delivery, ensuring accuracy and readability, patient-centeredness remains crucial. It is imperative to balance innovation with evidence-based practice.
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ISSN:0019-5049
0976-2817
DOI:10.4103/ija.ija_204_24