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Validity and reliability of artificial intelligence chatbots as public sources of information on endodontics.
- Source :
- International Endodontic Journal; Mar2024, Vol. 57 Issue 3, p305-314, 10p
- Publication Year :
- 2024
-
Abstract
- Aim: This study aimed to evaluate and compare the validity and reliability of responses provided by GPT‐3.5, Google Bard, and Bing to frequently asked questions (FAQs) in the field of endodontics. Methodology: FAQs were formulated by expert endodontists (n = 10) and collected through GPT‐3.5 queries (n = 10), with every question posed to each chatbot three times. Responses (N = 180) were independently evaluated by two board‐certified endodontists using a modified Global Quality Score (GQS) on a 5‐point Likert scale (5: strongly agree; 4: agree; 3: neutral; 2: disagree; 1: strongly disagree). Disagreements on scoring were resolved through evidence‐based discussions. The validity of responses was analysed by categorizing scores into valid or invalid at two thresholds: The low threshold was set at score ≥4 for all three responses whilst the high threshold was set at score 5 for all three responses. Fisher's exact test was conducted to compare the validity of responses between chatbots. Cronbach's alpha was calculated to assess the reliability by assessing the consistency of repeated responses for each chatbot. Results: All three chatbots provided answers to all questions. Using the low‐threshold validity test (GPT‐3.5: 95%; Google Bard: 85%; Bing: 75%), there was no significant difference between the platforms (p >.05). When using the high‐threshold validity test, the chatbot scores were substantially lower (GPT‐3.5: 60%; Google Bard: 15%; Bing: 15%). The validity of GPT‐3.5 responses was significantly higher than Google Bard and Bing (p =.008). All three chatbots achieved an acceptable level of reliability (Cronbach's alpha >0.7). Conclusions: GPT‐3.5 provided more credible information on topics related to endodontics compared to Google Bard and Bing. [ABSTRACT FROM AUTHOR]
- Subjects :
- ARTIFICIAL intelligence
CHATBOTS
INFORMATION resources
ENDODONTICS
LANGUAGE models
Subjects
Details
- Language :
- English
- ISSN :
- 01432885
- Volume :
- 57
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- International Endodontic Journal
- Publication Type :
- Academic Journal
- Accession number :
- 175282178
- Full Text :
- https://doi.org/10.1111/iej.14014