Self-reported AI literacy and AI anxiety as correlates of AI attitudes among speech-language therapy students in Türkiye: a cross-sectional study - Şaziye Seçkin Yılmaz; Namık Yücel Birol (BMC Medical Education, 2026)
Abstract Background Self-reported artificial intelligence (AI) literacy and AI anxiety may be associated with how future speech-language therapists evaluate AI, but evidence specific to this population is limited. Methods This cross-sectional survey examined the independent associations of the observed self-reported AI-literacy composite and AI anxiety with positive and negative attitudes toward AI among 313 fourth-year undergraduate speech-language therapy students from 24 departments in Türkiye. The two dimensions of the General Attitudes towards Artificial Intelligence Scale were analysed separately. Multiple regression models adjusted for age, gender, frequency of AI use, self-directed AI learning, and clinical-purpose AI use; standard errors were clustered by department, and wild cluster bootstrap inference was used. Results The observed self-reported AI-literacy composite was associated with more positive attitudes (B = 0.433, β = 0.373, p < .001), whereas AI anxiety was not. AI anxiety was associated with more negative attitudes (B = − 0.624, β = −0.674, p < .001), whereas the observed composite was not. Clinical-purpose AI use showed a smaller association with less negative attitudes (B = 0.148, β = 0.121, bootstrap p = .003); the self-directed-learning estimate was inconclusive. The two focal associations remained consistent in direction and statistical interpretation and were broadly similar in magnitude across sensitivity analyses. Conclusions These findings describe concurrent adjusted associations rather than temporal or causal pathways and should be interpreted in light of the weak measurement structure of the AI-literacy instrument in this sample.