Evaluating the agreement between ChatGPT-4 and validated questionnaires in screening for anxiety and depression in college students: a cross-sectional study (Preprint)

Abstract

<sec> <title>UNSTRUCTURED</title> Background: The Chat Generative Pre-trained Transformer (ChatGPT), an artificial intelligence-based web application, has demonstrated substantial potential across various knowledge domains, particularly in medicine. This cross-sectional study assessed the validity and possible usefulness of the ChatGPT-4 in assessing anxiety and depression by comparing two questionnaires. Methods: This study tasked ChatGPT-4 with generating a structured interview questionnaire based on the validated Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder Scale-7 (GAD-7). This study utilized Spearman correlation analysis, Intra-class correlation coefficients (ICC), Youden’s index, receiver operating characteristic (ROC) and Bland-Altman plots to evaluate the consistency between scores from a ChatGPT-4 adapted questionnaire and those from a validated questionnaire. Results: A total of 200 college students participated. Cronbach’s α indicated acceptable reliability for both GPT-PHQ-9 (α = 0.75) and GPT-GAD-7 (α = 0.76). ICC values were 0.80 for PHQ-9 and 0.70 for GAD-7. Spearman’s correlation showed moderate associations with PHQ-9 (p = 0.63) and GAD-7 (p = 0.68). ROC curve analysis revealed optimal cutoffs of 9.5 for depressive symptoms and 6.5 for anxiety symptoms, both with high sensitivity and specificity. Conclusions: The questionnaire adapted by ChatGPT-4 demonstrated good consistency with the validated questionnaire. Future studies should investigate the usefulness of the ChatGPT designed questionnaire in different populations. </sec>

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