Readiness and Acceptance of Nursing Students Regarding AI-Based Health Care Technology on the Training of Nursing Skills in Saudi Arabia: Cross-Sectional Study

Abstract BackgroundThe rapid advancements in artificial intelligence (AI) technologies across various sectors, including health care, necessitate the need for a comprehensive understanding of their applications. Specifically, the acceptance and readiness of nursing students as...

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Main Authors: Kamlah AL-Olaimat, Basma Salameh, Rasha Abdulhalim Alqadi, Abeer Alruwaili, Manal Hakami, Hanay Huwaydi ALanazi, Tahani Maharem, Fadia Ahmed Abdelkader Reshia
Format: Article
Language:English
Published: JMIR Publications 2025-07-01
Series:JMIR Nursing
Online Access:https://nursing.jmir.org/2025/1/e71653
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author Kamlah AL-Olaimat
Basma Salameh
Rasha Abdulhalim Alqadi
Abeer Alruwaili
Manal Hakami
Hanay Huwaydi ALanazi
Tahani Maharem
Fadia Ahmed Abdelkader Reshia
author_facet Kamlah AL-Olaimat
Basma Salameh
Rasha Abdulhalim Alqadi
Abeer Alruwaili
Manal Hakami
Hanay Huwaydi ALanazi
Tahani Maharem
Fadia Ahmed Abdelkader Reshia
author_sort Kamlah AL-Olaimat
collection DOAJ
description Abstract BackgroundThe rapid advancements in artificial intelligence (AI) technologies across various sectors, including health care, necessitate the need for a comprehensive understanding of their applications. Specifically, the acceptance and readiness of nursing students as future health care professionals to adopt AI-based health care technologies, along with the factors influencing these attitudes, are critical for facilitating the effective integration of AI in health care settings. ObjectiveThis study aimed to assess the readiness and acceptance of nursing students regarding the use of AI-based health care technologies in the nursing skills training in Saudi Arabia. MethodsA descriptive cross-sectional research design was used. A convenience sampling technique was applied to recruit 322 participants. Data were collected between June and September 2023 using a self-administered questionnaire that included the technology readiness index (TRI) and the technology acceptance scale. ResultsApproximately 92.2% (297/322) of participants exhibited positive attitudes toward AI, and 74.8% (322) demonstrated innovativeness, indicating a generally favorable perception of AI. However, more than half of the students (59% [190/322] and 59.3% [191/322], respectively) reported feelings of discomfort and negative perceptions regarding AI use. Regarding TRI, 69.6% (224/322) of participants showed moderate readiness, while 30.4% (98/322) exhibited a high level of TRI. A substantial majority (320/322 99.4%) expressed acceptance of AI-based technologies in their training, with only 0.6% (2/322) reporting nonacceptance. Older students (aged >22 y) exhibited significantly higher levels of AI acceptance and readiness compared to younger students (PPPP ConclusionsThe findings indicate that nursing students demonstrated a generally positive level of readiness and acceptance toward the use of AI and related technologies in education and training. However, these levels remained moderate overall, highlighting the need to enhance awareness and deepen students’ understanding of AI’s potential to improve training effectiveness and health care quality.
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issn 2562-7600
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spelling doaj-art-d58b610eea564f908cf71fc8ce552ac02025-08-20T03:44:58ZengJMIR PublicationsJMIR Nursing2562-76002025-07-018e71653e7165310.2196/71653Readiness and Acceptance of Nursing Students Regarding AI-Based Health Care Technology on the Training of Nursing Skills in Saudi Arabia: Cross-Sectional StudyKamlah AL-Olaimathttp://orcid.org/0009-0007-9635-846XBasma Salamehhttp://orcid.org/0000-0003-1372-7199Rasha Abdulhalim Alqadihttp://orcid.org/0000-0002-1831-0029Abeer Alruwailihttp://orcid.org/0000-0003-3345-4300Manal Hakamihttp://orcid.org/0000-0002-4956-876XHanay Huwaydi ALanazihttp://orcid.org/0009-0002-9994-9381Tahani Maharemhttp://orcid.org/0000-0002-7134-8261Fadia Ahmed Abdelkader Reshiahttp://orcid.org/0000-0003-1838-595X Abstract BackgroundThe rapid advancements in artificial intelligence (AI) technologies across various sectors, including health care, necessitate the need for a comprehensive understanding of their applications. Specifically, the acceptance and readiness of nursing students as future health care professionals to adopt AI-based health care technologies, along with the factors influencing these attitudes, are critical for facilitating the effective integration of AI in health care settings. ObjectiveThis study aimed to assess the readiness and acceptance of nursing students regarding the use of AI-based health care technologies in the nursing skills training in Saudi Arabia. MethodsA descriptive cross-sectional research design was used. A convenience sampling technique was applied to recruit 322 participants. Data were collected between June and September 2023 using a self-administered questionnaire that included the technology readiness index (TRI) and the technology acceptance scale. ResultsApproximately 92.2% (297/322) of participants exhibited positive attitudes toward AI, and 74.8% (322) demonstrated innovativeness, indicating a generally favorable perception of AI. However, more than half of the students (59% [190/322] and 59.3% [191/322], respectively) reported feelings of discomfort and negative perceptions regarding AI use. Regarding TRI, 69.6% (224/322) of participants showed moderate readiness, while 30.4% (98/322) exhibited a high level of TRI. A substantial majority (320/322 99.4%) expressed acceptance of AI-based technologies in their training, with only 0.6% (2/322) reporting nonacceptance. Older students (aged >22 y) exhibited significantly higher levels of AI acceptance and readiness compared to younger students (PPPP ConclusionsThe findings indicate that nursing students demonstrated a generally positive level of readiness and acceptance toward the use of AI and related technologies in education and training. However, these levels remained moderate overall, highlighting the need to enhance awareness and deepen students’ understanding of AI’s potential to improve training effectiveness and health care quality.https://nursing.jmir.org/2025/1/e71653
spellingShingle Kamlah AL-Olaimat
Basma Salameh
Rasha Abdulhalim Alqadi
Abeer Alruwaili
Manal Hakami
Hanay Huwaydi ALanazi
Tahani Maharem
Fadia Ahmed Abdelkader Reshia
Readiness and Acceptance of Nursing Students Regarding AI-Based Health Care Technology on the Training of Nursing Skills in Saudi Arabia: Cross-Sectional Study
JMIR Nursing
title Readiness and Acceptance of Nursing Students Regarding AI-Based Health Care Technology on the Training of Nursing Skills in Saudi Arabia: Cross-Sectional Study
title_full Readiness and Acceptance of Nursing Students Regarding AI-Based Health Care Technology on the Training of Nursing Skills in Saudi Arabia: Cross-Sectional Study
title_fullStr Readiness and Acceptance of Nursing Students Regarding AI-Based Health Care Technology on the Training of Nursing Skills in Saudi Arabia: Cross-Sectional Study
title_full_unstemmed Readiness and Acceptance of Nursing Students Regarding AI-Based Health Care Technology on the Training of Nursing Skills in Saudi Arabia: Cross-Sectional Study
title_short Readiness and Acceptance of Nursing Students Regarding AI-Based Health Care Technology on the Training of Nursing Skills in Saudi Arabia: Cross-Sectional Study
title_sort readiness and acceptance of nursing students regarding ai based health care technology on the training of nursing skills in saudi arabia cross sectional study
url https://nursing.jmir.org/2025/1/e71653
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