Kannan Sridharan, Reginald P Sequeira
Artificial intelligence and medical education: application in classroom instruction and student assessment using a pharmacology & therapeutics case study
BMC medical education
although poor mental health veterinarians reported different countries data exist mental health austrian veterinary students study aimed provide first data broad range mental health indicators austrian veterinary students compare data austrian general population explore factors associated poor mental health total 291 n 430 858 female mean age 2314 369 years total austrian veterinary student population n 1477 students 821 females took part online survey conducted november 2022 january 2023 indicators mental health symptoms depression phq9 anxiety gad7 insomnia isi7 stress pss4 alcohol abuse cage disordered eating scoff compared general austrian population higher proportion veterinary students exceeded cutoffs clinically relevant mental health symptoms p 005 total 553 participating veterinary students exceeded cutoff moderate depressive symptoms 526 moderate anxiety symptoms 209 clinically relevant insomnia symptoms 793 highstress symptoms 228 symptoms alcohol abuse 386 symptoms disordered eating multivariable logistic regression including several sociodemographic health behavior studyrelated variables predictors revealed mental health symptoms veterinary students associated female gender older age low physical activity high smartphone usage desired specification small animal wildlife medicine conclusion austrian veterinary students experience high mental health burden teaching coping skills strategies improve mental hygiene implemented curricula veterinary education improve mental health veterinary profession