aceTRV-2026-2257Version 1 · Certified
Reason for this version
Certified into the record
Canonical text (the exact bytes fingerprinted)
TRUVACE RECORD VERSION record: TRV-2026-2257 version: 1 kind: certified reason: Certified into the record timestamp: 2026-10-26T04:24:01.562887Z status: published lens: p_space sector: education headline: Nursing Students' Awareness, Perceptions, and Attitudes Toward Artificial Intelligence in Healthcare: A Cross-Sectional Study in Erbil, Iraq dek: Background: Artificial intelligence is increasingly influencing healthcare delivery and nursing education. Understanding nursing students' perceptions is important for preparing future professionals to use AI responsibly. Objective: To assess nursing students' awareness, experiences, perceptions, and training needs concerning artificial intelligence in healthcare. Methods: A descriptive, survey-based study was conducted among 175 nursing students at Cihan University-Erbil, Iraq. Data were collected using a 22-it… gain_title: (none) problem_title: Only a minority of surveyed nursing students had formal AI training, and students worried that heavy reliance on AI could erode human nursing skills. trace_subject: (none) gain_reading: (none) gain_evidence: (none) problem_reading: Only a minority of surveyed nursing students had formal AI training, and students worried that heavy reliance on AI could erode human nursing skills. problem_evidence: Only 30.3% had received formal AI training | possible reductions in human nursing skills through excessive AI dependence quick_read: A descriptive survey at Cihan University-Erbil in Iraq asked 175 nursing students about their awareness, use, and views of artificial intelligence in healthcare. Most were aware of AI and over half had already used it, and many were optimistic about its potential for patient care and communication. The results suggest nursing programs may be sending students into AI-influenced workplaces without enough structured preparation. Because the study is a single-institution questionnaire of attitudes, it does not show how AI training affects actual clinical practice or patient outcomes. limitation: The study surveyed students at one university using descriptive statistics, and the authors recommend research involving multiple institutions. tag: Evidence-backed problem key_points: 81.7% of the 175 surveyed nursing students were aware of AI, and 56.6% reported having used it. | 64.6% thought deep learning-based AI could improve patient care. | 68.0% saw AI as a way to ease communication across language barriers. | Only 30.3% had formal AI training, while 63.4% said more training was necessary. rundown: The study used a 22-item closed-ended questionnaire with nursing students at Cihan University-Erbil, Iraq, and summarized the answers with descriptive statistics. Students were generally positive about AI applications, but they also raised concern that excessive dependence could reduce human nursing skills. The authors conclude that structured AI education, ethical guidance, and continued human oversight are needed, and they recommend further research across multiple institutions. sources: - peer_reviewed | International Journal of Science and Research (IJSR) | https://doi.org/10.21275/mr261022152029 | 2026-10-24 prev: 0000000000000000000000000000000000000000000000000000000000000000
- sha256
- 6560649252adb1d614fabdb63e5eb4db7a11a00b7c8201cb379c94e5c8c18d29
- previous
- 0000000000000000000000000000000000000000000000000000000000000000
Verify this record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-2257 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.