ChatGPT as a rising force: Can AI bridge information gaps in Occupational Risk Prevention?

Abstract

BackgroundLack of information is a critical challenge in occupational health. With over 180 million users, ChatGPT has become a prominent trend, swiftly addressing a wide array of queries, yet it critically needs validation in occupational health.ObjectiveThis study evaluated GPT-3.5 (free version) and GPT-4 (paid version) on their ability to respond to Occupational Risk Prevention formal multiple-choice questions.MethodsA total of 303 questions were assessed, categorized across four levels of complexity-task-specific, national, European, and global-within various Spanish regions.ResultsGPT-3.5 achieved an overall accuracy of 56.8%, while GPT-4 reached 73.9% (p < 0.001). GPT-3.5 showed particularly limited performance on domain-specific content. Both models shared similar error patterns, with incorrect response rates ranging from 18-24% across regions.ConclusionDespite GPT-4's improved performance, both models display notable limitations in occupational health applications. To enhance reliability, four strategies are proposed: formal validation, continuous training, error analysis, and regional adaptation.