Awareness of academic paper retractions and artificial intelligence–related risks among health researchers in Jordan: a cross-sectional study

Abstract

Purpose: This study assessed awareness of academic paper retractions and artificial intelligence (AI)-related risks among health researchers in Jordan. Methods: This cross-sectional study was conducted from February to March 2026 among 255 health researchers in Jordan using a structured, validated online questionnaire. The questionnaire assessed demographic and professional characteristics, awareness of academic paper retractions, retraction-related perceptions and practices, and AI tool use. Results: A high proportion of respondents were aware of academic paper retractions (76.9%). Respondents reported that the most frequent reasons for retractions of published articles were data fabrication (90.6%) and improper use of AI tools (82.4%). Despite this awareness, 61.2% never or rarely checked whether articles cited in their manuscripts had been retracted before manuscript submission. Overall, 73.3% of respondents reported using AI tools. The main concerns about AI tool use were fabricated references (83.9%) and fabricated data (80.4%). Most participants (88.2%) believed that AI misuse is likely to increase retractions. Having> 10 publications was the only significant predictor of awareness (adjusted odds ratio, 3.114; 95% confidence interval, 1.220�7.949). Conclusion: Although awareness of retractions was relatively high, gaps in verification practices and widespread AI use may pose risks to research integrity. Targeted publication ethics training is needed, particularly for early-career researchers.