Survey reveals heavy artificial intelligence usage links to increased impostor feelings and mental health distress among social work students, highlighting urgent needs for ethical guidelines.
The rising use of artificial intelligence tools in academic research presents a paradox for social work education. On one hand, AI assistance can ease workloads and spark creativity; on the other, it raises ethical dilemmas and may impact student mental health. This study examines how AI tool usage relates to imposter syndrome and mental health (anxiety, stress, and depression) among final-year social work students in Kerala, India. We surveyed 208 students about their AI use patterns, motivations, and ethical concerns and measured their imposter feelings and mental health. Results show that while a majority use AI for research tasks, many raise concerns about academic integrity and AI-generated content. Students highly dependent on AI reported significantly greater imposter syndrome and higher anxiety, stress, and depression levels than those with low AI reliance. Ordinal logistic regression showed that AI detection anxiety, along with general anxiety, heavy use of AI, and dissatisfaction with AI’s accuracy, were strong indicators of imposter phenomenon. These findings highlight a critical tension between embracing technological innovation and upholding academic and professional integrity. We discuss implications for social work education, recommending proactive ethics training around AI, support for student well-being, and clear guidelines on acceptable AI use.
No takes yet. Share an insight, caveat, or question.
Odathakkal et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: