Midwifery Students’ Adaptation to Artificial Intelligence
This study aims to investigate the relationships between self-leadership, digital literacy, attitudes towards the professional development, and readiness for artificial intelligence among midwifery students. This correlational study was conducted between March 1st and April 30th, 2023, and included 405 midwifery students in Türkiye. The study aimed to assess the readiness of midwifery students in Türkiye for the integration of artificial intelligence in healthcare. Data were collected using the Medical Artificial Intelligence Readiness Scale for Medical Students, Self-Leadership Questionnaire, Attitude Scale for Professional Development, and Digital Literacy Scale. The study found that self-leadership, attitudes towards professional development, and digital literacy were significant factors in explaining midwifery students' readiness for artificial intelligence. Furthermore, the results indicated that self-leadership has a positive impact on readiness for artificial intelligence by promoting attitudes towards professional development and digital literacy. The readiness of midwifery students for artificial intelligence is determined by their self-leadership, attitude towards professional development, and digital literacy. These findings can guide the organization of teaching programs in midwifery, the development of intervention programs, and the adaptation of midwifery students to technology to enhance their practices.
Authors
- Osman Tayyar Çelik (ORCID: https://orcid.org/0000-0003-3951-7261)
- Tuba Uçar
- Sümeyye Barut
- Esra Sabanci Baransel
Institutions
- Fırat University (TR)
- Inonu University (TR)
- Society for Research in Child Development (US)
- University Child Development School (US)
- Child Development Center (QA)
Publication Details
- Journal
- CIN Computers Informatics Nursing
- Published
- 2026-01-09
- DOI
- https://doi.org/10.1097/cin.0000000000001374
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00