Background Artificial intelligence (AI) is increasingly shaping daily decision-making by enhancing efficiency and consistency. However, prolonged AI use may impose cognitive strain, attention depletion, information overload, and decision fatigue. Aim To investigate the relationships among AI anxiety, attitudes toward AI, cognitive performance, trust in AI, and decision fatigue, particularly emphasising long-term AI interaction. Methods A structured survey was administered both online and offline to a sample of 500 adults (290 males, 210 females) in the Delhi–NCR region, with a mean age of 24.2 ± 3.4 years. The survey assessed participant’s AI anxiety, AI attitude, cognitive skills, decision fatigue, and trust (encompassing reliability, productivity, and user control). Descriptive statistics and Pearson correlation analyses were conducted to explore the relationships between these variables. Result Participants reported moderately high AI anxiety (mean = 4.62, SD = 1.14) and generally positive attitudes toward AI (mean = 5.01, SD = 1.06). A strong but marginally non-significant correlation ( r = 0.81, p = .053) was found between favourable attitudes and technology usage frequency. High trust in AI—measured via reliability ( r = 0.597), productivity ( r = 0.985), and control ( r = 0.829)—correlated with prior positive AI experience. Long-term AI use was significantly associated with mental exhaustion, attention strain, and information overload ( r = 0.905), and inversely associated with decision-making self-confidence ( r = −0.360). Conclusion The integration of AI in task performance resulted in improved efficiency and user confidence; however, prolonged utilisation may precipitate cognitive fatigue, diminished focus, and attenuated user agency. To mitigate these adverse effects, strategic design approaches prioritising user empowerment, transparency, and cognitive facilitation are essential for maximising benefits while upholding mental health and well-being.
Shalu et al. (Wed,) studied this question.