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
Abstract Background The 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. Objective This 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. Methods A 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. Results Approximately 92.2% (297/322) of participants exhibited positive attitudes toward AI, and 74.8% (241/322) 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…
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 322 participants or records.
Read the paper
Related studies
- Improving sleep quality leads to better mental health: A meta-analysis of randomised controlled trials
- Tocilizumab in patients with severe COVID-19: a retrospective cohort study
- A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV: A cohort study
- Fruit, vegetable, and legume intake, and cardiovascular disease and deaths in 18 countries (PURE): a prospective cohort study
- Are noise and air pollution related to the incidence of dementia? A cohort study in London, England
- Long COVID symptoms and duration in SARS-CoV-2 positive children — a nationwide cohort study
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.