Abstract

We aimed to describe the prevalence, frequency, and purposes of artificial intelligence (AI) tool use among child and adolescent psychiatrists and residents in Türkiye, and to examine perceived benefits, risks, child/adolescent-specific concerns, and approval of patient/parent mental health–related use outside clinical settings. We conducted an anonymous, cross-sectional online survey (November–December 2025) distributed through national professional WhatsApp groups (convenience sample). The survey assessed sociodemographic/professional variables, technology readiness, AI tool use (ever/regular use, frequency), purposes of use across common tasks, and attitudes/perceptions rated on Likert scales. Composite scores were created for perceived benefits/risks, child/adolescent-specific concerns, and approval of out-of-clinic mental health uses; associations were examined with Spearman correlations. Of 100 initiated responses, 88 complete responses were analyzed (mean age 32.5 years; 76.1% female). ChatGPT was the most commonly used AI tool in our sample: nearly all participants (98.9%) had used it before. 93.2% reported regular professional/educational use of at least one AI tool (ChatGPT: 90.9%). Formal AI training was uncommon (5.7%). Most respondents used AI at least weekly (84.1%), and nearly half used it daily (46.6%). The most frequent purposes were preparing educational materials, accessing up-to-date information, and literature scanning, whereas clinical decision support and medicolegal documentation were less common. Participants reported moderate endorsement of both benefits and risks, high child/adolescent-specific concerns, and comparatively low approval of out-of-clinic mental health uses, with the highest endorsement for therapist-supervised adjunctive use and the lowest for medication or treatment advice. More frequent AI use was associated with higher self-rated AI knowledge, greater perceived benefits and approval, and lower child/adolescent-specific concerns. AI tool use is widespread among child and adolescent psychiatrists in Türkiye despite minimal formal training, suggesting a training-and-governance gap. Use is primarily oriented toward education and knowledge-support tasks, while substantial child/adolescent-specific concerns persist. Patient-facing applications appear most acceptable when supervised; guidance and competency-based training are needed to support safe, bounded implementation.

Key words: Artificial Intelligence, natural language processing, child psychiatry, adolescent psychiatry