AI Chatbots and Online Health Information Use in Self-Medication Among University Students in Lahore, Pakistan: A Cross-Sectional Study
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Background: Self-medication among university students is a growing public health concern, particularly in settings where prescription medicines are easily accessible and digital health information is widely used. The rapid adoption of AI chatbots and online platforms may further influence self-diagnosis and self-prescription practices. Objective: To determine the prevalence and pattern of self-medication among university students in Lahore, Pakistan, and assess its association with AI chatbot and internet-based health information use. Methods: A cross-sectional descriptive-analytical study was conducted among 451 medical and non-medical university students in Lahore. Data were collected using a structured self-administered questionnaire assessing sociodemographic characteristics, AI and internet use, self-medication practices, knowledge, attitudes, drug categories, adverse effects, and actions after adverse effects. Associations were analyzed using chi-square tests, odds ratios, 95% confidence intervals, and effect sizes where applicable. Results: Online symptom searching was reported by 363 students (80.5%), internet-based self-diagnosis by 319 (70.7%), and online self-prescription by 254 (56.3%). Medical students had higher odds of online symptom searching, internet-based self-diagnosis, online self-prescription, and antibiotic self-medication. Antibiotics were the most common self-medicated drug category (51.4%), and adverse effects were reported by 255 students (56.5%). Conclusion: AI and internet-based health information use is highly prevalent and associated with self-medication behaviors among university students in Lahore. Targeted AI health literacy, antimicrobial stewardship education, and stronger regulation of prescription-only medicines are needed.
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