Background and objective ChatGPT and Google Bard AI are widely used conversational chatbots, even in healthcare. While they have several strengths, they can generate seemingly correct but erroneous responses, warranting caution in medical contexts. In an era where access to abortion care is diminishing, patients may increasingly rely on online resources and AI-driven language models for information on medication abortions. In light of this, this study aimed to compare the accuracy and comprehensiveness of responses generated by ChatGPT 3.5 and Google Bard AI to medical queries about medication abortions. Methods Fourteen open-ended questions about medication abortion were formulated based on the Frequently Asked Questions (FAQs) from the National Abortion Federation (NAF) and the Reproductive Health Access Project (RHAP) websites. These questions were answered using ChatGPT version 3.5 and Google Bard AI on October 7, 2023. The accuracy of the responses was analyzed by cross-referencing the generated answers against the information provided by NAF and RHAP. Any discrepancies were further verified against the guidelines from the American Congress of Obstetricians and Gynecologists (ACOG). A rating scale used by Johnson et al. was employed for assessment, utilizing a 6-point Likert scale [ranging from 1 (completely incorrect) to 6 (correct)] to evaluate accuracy and a 3-point scale [ranging from 1 (incomplete) to 3 (comprehensive)] to assess completeness. Questions that did not yield answers were assigned a score of 0 and omitted from the correlation analysis. Data analysis and visualization were done using R Software version 4.3.1. Statistical significance was determined by employing Spearman's R and Mann-Whitney U tests. Results All questions were entered sequentially into both chatbots by the same author. On the initial attempt, ChatGPT successfully generated relevant responses for all questions, while Google Bard AI failed to provide answers for five questions. Repeating the same question in Google Bard AI yielded an answer for one; two were answered with different phrasing; and two remained unanswered despite rephrasing. ChatGPT showed a median accuracy score of 5 (mean: 5.26, SD: 0.73) and a median completeness score of 3 (mean: 2.57, SD: 0.51). It showed the highest accuracy score in six responses and the highest completeness score in eight responses. In contrast, Google Bard AI had a median accuracy score of 5 (mean: 4.5, SD: 2.03) and a median completeness score of 2 (mean: 2.14, SD: 1.03). It achieved the highest accuracy score in five responses and the highest completeness score in six responses. Spearman's correlation coefficient revealed no correlation between accuracy and completeness for ChatGPT (rs = -0.46771, p = 0.09171). However, Google Bard AI showed a marginally significant correlation (rs = 0.5738, p = 0.05108). Mann-Whitney U test indicated no statistically significant differences between ChatGPT and Google Bard AI concerning accuracy (U = 82, p>0.05) or completeness (U = 78, p>0.05). Conclusion While both chatbots showed similar levels of accuracy, minor errors were noted, pertaining to finer aspects that demand specialized knowledge of abortion care. This could explain the lack of a significant correlation between accuracy and completeness. Ultimately, AI-driven language models have the potential to provide information on medication abortions, but there is a need for continual refinement and oversight.
Keywords: artificial intelligence; chatbots; chatgpt; ethics; google bardai; large language models; medication abortion; patient information.
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