The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index; 1 of the 24 sources its claims cite were checked for support.
Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice
Open accessAbstract
Introduction: Worldwide, healthcare systems aim to achieve the best possible quality of care at an affordable cost while ensuring broad access for all populations. The use of artificial intelligence (AI) in healthcare holds promise to address these challenges through the integration of real-world data-driven insights into patient care processes. This study aims to assess nurses’ awareness and attitudes toward AI-integrated tools used in clinical practice. Methods: A descriptive cross-sectional design captured nurses’ responses at three governmental hospitals in Saudi Arabia by using an online questionnaire administered over 4 months. The study involved 220 registered nurses with a minimum of one year of clinical experience, selected through a convenience sampling method. The online survey consisted of three sections: demographic information, an assessment of nurses’ AI knowledge, and the general attitudes toward the AI scale. Results: Nurses displayed “moderate” levels of awareness toward AI technology, with 70.9% having basic information about AI and only 58.2% (128 nurses) were considered “aware” of AI as they dealt with one of its healthcare applications. Nurses expressed openness to AI integration ( M = 3.51) on one side, but also had some concerns about AI. Nurses expressed conservative attitudes toward AI, with significant differences observed based on gender (χ² = 4.67, p < 0.05). Female nurses exhibited a higher proportion of negative attitudes compared to male nurses. Significant differences were also found based on age (χ² = 9.31, p < 0.05), with younger nurses demonstrating more positive attitudes toward AI compared to their older counterparts. Educational background yields significant differences (χ² = 6.70, p < 0.05), with nurses holding undergraduate degrees exhibiting the highest positive attitudes. However, years of nursing experience did not reveal significant variations in attitudes. Conclusion: Healthcare and nursing administrators need to work on increasing the nurses’ awareness of AI applications and emphasize the importance of integrating such technology into the systems in use. Moreover, addressing nurses’ concerns about AI's control and discomfort is crucial, especially considering generational differences, with younger nurses often having more positive attitudes toward technology. Change management strategies may help overcome any hindrances.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
This cross-sectional survey of 220 Saudi registered nurses found moderate AI awareness and generally conservative attitudes toward AI in clinical practice. Demographic factors—gender, age, and education—were significantly associated with attitudes, while years of nursing experience were not.
Key findings
- Awareness was moderate: 70.9% reported basic information about AI, 67.3% had heard of AI in medicine, and 58.2% (128 nurses) reported encountering/using AI means in the medical field.
- Nurses showed some openness to AI, including interest in using AI in daily life (M = 3.51) and willingness to use AI in their job (M = 3.50), but also concerns about AI control (M = 3.15), personal consequences (M = 3.10), errors (M = 3.04), discomfort about future uses (M = 3.02), and danger (M = 2.93).
- Significant attitude differences were found by gender (χ² = 4.67, p < 0.05), with more female nurses expressing negative attitudes (41.4%) than male nurses (10.5%); by age (χ² = 9.31, p < 0.05), with 20–29-year-olds most positive (20.5%) and 50–59-year-olds least positive (2.7%); and by education (χ² = 6.70, p < 0.05), with undergraduate-degree nurses most positive (32.3%), followed by postgraduate (17.4%) and diploma nurses (5%).
- Years of nursing experience showed no significant variation in attitudes (χ² = 2.67, p = 0.61).
Methods
- Descriptive cross-sectional online survey conducted in three governmental hospitals in the Jouf region, northern Saudi Arabia, over four months (April–September 2023).
- Convenience sample of 220 registered nurses with at least one year of clinical experience; about 350 nurses were invited, yielding a 62.9% response rate.
- Instrument included demographics, a 7-item “Yes/No” Nurses’ AI knowledge questionnaire (Cronbach’s alpha 0.795), and the 20-item General Attitudes toward AI Scale (GAAIS; 5-point Likert; positive subscale alpha 0.88, negative subscale alpha 0.82). Analysis used descriptive statistics and chi-squared tests.
Limitations
- The paper states that generalization is limited because the study was restricted to nursing professionals in a specific setting and used a cross-sectional design; it recommends longitudinal and qualitative studies including nurses and other healthcare workers.
- Evident from the text: convenience sampling, self-report online survey, and recruitment from only three governmental hospitals in one northern Saudi region limit generalizability.
- Evident from the text: the sample was predominantly female (73.6%), and AI awareness was assessed largely through “Yes/No” items, which may not capture depth of knowledge.
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28 Own result · 15 Not checked yet · 4 Own method · 2 Own interpretation · 1 Partly supported · accuracy not yet measured
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In the paper
“As for nurses, many gaps still exist where nurses are not yet involved in the process of developing, integrating, and implementing AI in healthcare, especially since they are among the most involved professions with AI technology applications and functions. 13”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Introduction
What the sources say
- Partly supportedcites [13] Ronquillo CE Peltonen LM Pruinelli L, et al. Artificial intelligence in nursing: priorities and opportunities from an international invitational think-tank of the nursing and artificial intelligence leadership collaborative. J Adv Nurs 2021; 77: 3707– 3717. 34003504 PMC7612744 sourceExperimental — accuracy not yet measured
In Discussion, Priority 2 (page unavailable), the paper says nurses are often end-users of AI technologies rather than collaborators in their development, and calls for their involvement from development through implementation. This supports the stated gap, but the cited paper does not establish the sentence’s further claim that nurses are among the professions most involved with AI applications and functions. (LLM, conf=0.85)
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Nurses displayed “moderate” levels of awareness toward AI technology, with 70.9% having basic information about AI and only 58.2% (128 nurses) were considered “aware” of AI as they dealt with one of its healthcare applications.”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Abstract > Results
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Nurses expressed openness to AI integration (M = 3.51) on one side, but also had some concerns about AI.”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Abstract > Results
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In the paper
“Furthermore, 40.0% of nurses reported encountering AI in nursing diagnosis through electronic care systems, and 45.5% reported that they had used AI to calculate drug doses.”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Results > Nurses’ awareness toward AI
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In the paper
“the mean score for the item “I would like to use AI in my job” was 3.50 (SD = 0.99)”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Discussion
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In the paper
“Female nurses exhibited a higher proportion of negative attitudes compared to male nurses.”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Abstract > Results
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In the paper
“Just above half (58.2%) of the participating nurses demonstrated practical knowledge of AI-integrated technology.4,5,13”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Discussion
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In the paper
“Nurses expressed openness to AI integration (M = 3.51) on one side, but also had some concerns about AI.”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Abstract > Results
plain- Asserted: passes — The authors put it forward as true.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Furthermore, 40.0% of nurses reported encountering AI in nursing diagnosis through electronic care systems, and 45.5% reported that they had used AI to calculate drug doses.”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Results > Nurses’ awareness toward AI
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“In terms of educational background, 39.1% of nurses reported that the basics of AI were covered in their undergraduate education, while the majority (60.9%) stated otherwise.”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Results > Nurses’ awareness toward AI
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- It may state two separate claims as one. 12
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“nurses with undergraduate degrees demonstrated the highest positive attitude toward AI (32.3%), followed by postgraduate degree holders (17.4%), and those with diplomas (5%). Significant differences were observed among educational levels (χ² = 6.70, p < 0.05).”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Results > Differences in nurses’ attitudes toward AI
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In the paper
“nurses aged 20–29 years demonstrated the highest positive attitude toward AI (20.5%), whereas those aged 50–59 years exhibited the lowest (2.7%). Statistically significant differences were found across age categories (χ² = 9.31, p < 0.05).”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Results > Differences in nurses’ attitudes toward AI
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In the paper
“Nurses expressed conservative attitudes toward AI, with significant differences observed based on gender (χ² = 4.67, p < 0.05).”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Abstract > Results
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“a higher proportion of female nurses (41.4%) expressed negative attitudes toward AI compared to male nurses (10.5%), with statistically significant differences (χ² = 4.67, p < 0.05).”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Results > Differences in nurses’ attitudes toward AI
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“Additionally, the GAAIS exhibited good convergent and divergent validity with a related scale.23,24”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Methods > Instrument
What the sources say
- Not checked yetcites [23] Schepman A Rodway P. Initial validation of the general attitudes towards artificial intelligence scale. Comput Hum Behav Rep 2020; 1: 100014. 34235291 PMC7231759 source
- Not checked yetcites [24] Schepman A Rodway P. The general attitudes towards artificial intelligence scale (GAAIS): confirmatory validation and associations with personality, corporate distrust, and general trust. Int J Hum Comput 2023; 39: 2724– 2741. source
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“The GAAIS demonstrated good internal consistency, with Cronbach alpha values of 0.88 for the Positive GAAIS (12 items) and 0.82 for the Negative GAAIS (8 items), as reported by Schepman and Rodway. 24”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Methods > Instrument
What the sources say
- Not checked yetcites [24] Schepman A Rodway P. The general attitudes towards artificial intelligence scale (GAAIS): confirmatory validation and associations with personality, corporate distrust, and general trust. Int J Hum Comput 2023; 39: 2724– 2741. source
boosted- Asserted: passes — The authors put it forward as true.
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In the paper
“AI could help solve some of the problems facing the nursing profession, such as job dissatisfaction and unintended deficiencies in patient care (such as errors in the administration of medication and identification of at-risk clients).15,17”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Introduction
What the sources say
- Not checked yetcites [15] Robert N. How artificial intelligence is changing nursing. Nurs Manage 2019; 50: 30– 39. PMC7597764 31425440 source
- Not checked yetcites [17] Alluhidan M Tashkandi N Alblowi F, et al. Challenges and policy opportunities in nursing in Saudi Arabia. Hum Resour Health 2020; 18: 1– 10. 33276794 PMC7716289 source
hedgedconditional- Asserted: passes — The authors put it forward as true.
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In the paper
“Missing data were handled by excluding cases with incomplete responses from the analysis.”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Methods > Data collection
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In the paper
“Female nurses and those older than 50 years demonstrated more conservative attitudes compared to their counterparts, with χ2 values of 4.67, p < 0.05, and 9.31, p < 0.05, respectively.”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Discussion
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In the paper
“The study obtained approval from the Bioethics Institutional Review Board at Jouf University (Approval no. 3-06-44, 7 February 2023), adhering to the principles outlined in the Helsinki Declaration. 25”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Methods > Ethical consideration
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In the paper
“However, a total of 220 nurses participated in the study, providing complete responses to the questionnaire, exceeding the anticipated recruitment target.”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Methods > Sampling and setting
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In the paper
“Conservative attitudes toward AI may stem from various concerns, including fears about job displacement, doubts about AI's reliability and accuracy, and ethical worries about patient privacy and the depersonalization of care.7,26”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Discussion
What the sources say
- Not checked yetcites [7] O’Connor S Yan Y Thilo FJ, et al. Artificial intelligence in nursing and midwifery: a systematic review. J Clin Nurs 2023; 32: 2951– 2968. 35908207 source
- Not checked yetcites [26] Alhashmi S Salloum SA Mhamdi C. Implementing artificial intelligence in the United Arab Emirates healthcare sector: an extended technology acceptance model. Int J Inf Technol Lang Stud 2019; 3: 27– 42.
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In the paper
“Nurses who have positive views and attitudes toward AI are more likely to feel comfortable using AI applications and they view AI and other technology applications as useful and easy to use.28,29”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Discussion
What the sources say
- Not checked yetcites [28] Park J Woo SE. Who likes artificial intelligence? Personality predictors of attitudes toward artificial intelligence. J Psychol 2022; 156: 68– 94. 35015615 source
- Not checked yetcites [29] Bozak MG. Using Lewin’s force field analysis in implementing a nursing information system. Comput Inform Nurs 2003; 21: 80– 85. 12802948 source
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In the paper
“These conservative attitudes are particularly pronounced among female and older nurses, suggesting that demographic factors play a crucial role in shaping perceptions of technological advancements.7,26,30”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Discussion
What the sources say
- Not checked yetcites [7] O’Connor S Yan Y Thilo FJ, et al. Artificial intelligence in nursing and midwifery: a systematic review. J Clin Nurs 2023; 32: 2951– 2968. 35908207 source
- Not checked yetcites [26] Alhashmi S Salloum SA Mhamdi C. Implementing artificial intelligence in the United Arab Emirates healthcare sector: an extended technology acceptance model. Int J Inf Technol Lang Stud 2019; 3: 27– 42.
- Not checked yetcites [30] Hwang G-J Tang K-Y Tu Y-F. How artificial intelligence (AI) supports nursing education: profiling the roles, applications, and trends of AI in nursing education research (1993–2020). Inter Learn Environ 2024; 1: 373– 392. source
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In the paper
“This can be explained by the thoughts of nurses about the changes that can be introduced to their role in practice settings as AI-integrated technology may affect the decision-making process and lead nurses and other healthcare practitioners in that. 12”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Discussion
What the sources say
- Not checked yetcites [12] Clancy TR. Artificial intelligence and nursing: the future is now. J Nurs Adm 2020; 50: 125– 127. 32068622 source
hedgedconditional- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The changing role of nurses may introduce anxiety toward AI, 27 which directly affects the attitudes toward AI and the resulting potential difficulties in future adoption and usage of its applications in practice in addition to the concern of invaded privacy that may result from some AI-integrated technology applications. 27”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Discussion
What the sources say
- Not checked yetcites [27] Esmaeilzadeh P. Use of AI-based tools for healthcare purposes: a survey study from consumers’ perspectives. BMC Med Inform Decis Mak 2020; 20: 1– 19. 32698869 PMC7376886 source
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In the paper
“Caution should be practiced in the generalization of the current study results as it is limited to nursing professionals in a specific setting in addition to its cross-sectional nature.”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Limitations and recommendations
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may state two separate claims as one.
The paper relies on this without support.
The use of AI is not yet well understood among Saudi Arabian nurses, and little is known about their readiness, confidence, attitudes, and barriers to embracing AI in the clinical setting.
“The use of AI is not yet well understood among Saudi Arabian nurses, as little is known about their readiness, confidence, attitudes, and barriers to embracing AI in the clinical setting.”
The paper relies on this without support.
Nursing professionals may lack the knowledge, skills, and confidence to see the utilization of AI and digital health approaches, which explains why these resources aren’t utilized, or viewed as utilized, widely.
“Nursing professionals may lack the knowledge, skills, and confidence to see the utilization of AI and digital health approaches, which explains why these resources aren’t utilized, or viewed as utilized, widely.”
The paper relies on this without support.
Nurses are the end users of AI technology and interact directly with patients.
“Because nurses are the end users of the technology and interact directly with patients, it is critical to assess their current understanding of AI to determine future training needs. 21”
The paper relies on this without support.
AI and other technology applications are becoming part of nurses' daily work.
“Nurses need to be introduced to the imminent transformation of nursing practice as AI and other technology applications are becoming part of their daily work for nurses.”
The paper relies on this without support.
Nurses' roles and functions are being assisted by the different applications of technology including AI.
“Nurses’ roles and functions are being assisted by the different applications of technology including AI.”
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In the citing paper
“One descriptive study assessing nurses’ awareness and attitudes toward AI in clinical practice met four criteria due to a limited sample drawn from three hospitals, despite the use of validated tools and an adequate response rate (40).”
From Artificial intelligence in nursing: an integrative review of clinical and operational impacts (2025) · cites this paper as [40]
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In the paper
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Methods > Sampling and setting
“The inclusion criteria for participants involved registered nurses in Saudi Arabia with at least one year of clinical experience”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Results > Sample characteristics
“| Years of nursing experience | <1 year | 28 | 12.7 |”
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In the paper
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Results > Differences in nurses’ attitudes toward AI
“| Gender | Male | 23 | 10.5 | 35 | 15.9 | χ² = 4.67*p = 0.03 | | Gender | Female | 91 | 41.4 | 71 | 32.2 | χ² = 4.67*p = 0.03 |”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Results > Differences in nurses’ attitudes toward AI
“| Age | 20–29 years | 15 | 7 | 45 | 20.5 | χ² = 9.31*p = 0.02 | | Age | 30–39 years | 55 | 25 | 65 | 29.5 | χ² = 9.31*p = 0.02 | | Age | 40–49 years | 12 | 5.5 | 14 | 6.3 | χ² = 9.31*p = 0.02 | | Age | 50–59 years | 8 | 3.5 | 6 | 2.7 | χ² = 9.31*p = 0.02 |”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Results > Sample characteristics
“over half of the participants”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Results > Sample characteristics
“(45%) had a decade or more of experience”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Methods > Data collection
“The data was collected over four months”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Methods > Data collection
“(April to September 2023)”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
“| Marital status | Single | 84 | 37.3 |”
§ Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice > Results > Sample characteristics
Reported 37.3 · recomputed 38.181818
Citations
Cites
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“24 Additionally, the GAAIS exhibited good convergent and divergent validity with a related scale.”
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“4,5,13 This highlights the importance of integrating AI-related terminology and applications into the nursing educational programs and the continuous education efforts for practicing nurses; which may extend to other healthcare workers as well.”
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Tun, H. M., Rahman, H. A., Naing, L., & Malik, O. A. (2025) · Journal of Medical Internet Research · doi:10.2196/69678 · Cited by 210
“Trust has also been studied in the context of upstream relationships among different stakeholders [4,8-10 , 12].”
The Role of AI in Nursing Education and Practice: Umbrella Review
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“There is a pressing need to equip nurses with the knowledge and skills to critically assess AI technologies, understand their limitations, and collaborate effectively with these systems [13].”
Self-citationArtificial intelligence in nursing: an integrative review of clinical and operational impacts
Hassanein, S., El Arab, R. A., Abdrbo, A., Abu-Mahfouz, M. S., Gaballah, M. K. F., Seweid, M. M., Almari, M., & Alzghoul, H. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1552372 · Cited by 134
El Arab, R. A., Alshakihs, A. H., Alabdulwahab, S. H., Almubarak, Y. S., Alkhalifah, S. S., Abdrbo, A., Hassanein, S., & Sagbakken, M. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1666005 · Cited by 113
El-Sayed, B. K. M., El‐Sayed, A. A. I., Alsenany, S. A., & Asal, M. G. R. (2024) · Nurse Education in Practice · doi:10.1016/j.nepr.2024.104208 · Cited by 136
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“%) of the participants had any practical knowledge of AI-integrated technology [146].”
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Rony, M. K. K., Akter, K., Nesa, L., Islam, M. T., Johra, F. T., Akter, F., Uddin, M. J., Begum, J., Noor, M. A., Ahmad, S., et al. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e40775 · Cited by 72
“This is a concerning observation given the growing role of AI in healthcare [46].”
Atalla, A. D. G., El-Gawad Mousa, M. A., Hashish, E. A. A., Elseesy, N. A. M., Abd El kader Mohamed, A. I., & Sobhi Mohamed, S. M. (2025) · BMC Nursing · doi:10.1186/s12912-025-03306-3 · Cited by 58
“Research highlights significant gaps in AI readiness, with studies showing that many nurses lack understanding of AI’s role in clinical settings, contributing to hesi-tancy in AI adoption [19].”
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“This result is consistent with research by Alruwaili et al. which highlighted variations in attitudes toward AI among nurses based on their education level [19].”
ResultNurses perceptions and use of artificial intelligence in healthcare
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“In contrast, the results of some studies showed high level of high knowledge of artificial intelligence in the nurses, which is not consistent with the results of our study 27,28 .”
Ibrahim, A. M., Zoromba, M. A., Abousoliman, A. D., Zaghamir, D. E. F., Alenezi, I. N., Elsayed, E. A. H., & Mohamed, H. A. H. (2025) · BMC Nursing · doi:10.1186/s12912-025-02798-3 · Cited by 36
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“In addition, Alruwaili et al. evaluated nurses’ awareness and attitudes toward AI tools in clinical settings [13].”
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“Studies indicate that nurses who perceive AI positively are more likely to use it effectively, improve clinical accuracy, and enhance patient safety [11, 24].”
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“This is consistent with the results of a survey on AI literacy of nursing staff [51].”
Batran, A., Ayed, A., Aqtam, I. F., Al-Amer, R. M., Othman, E. H., Ejheisheh, M. A., daamsa, H. N. A., Alkhatib, S. G., & Farajallah, M. (2025) · SAGE Open Nursing · doi:10.1177/23779608251376177 · Cited by 12
“Similarly, research in Saudi Arabia revealed that nurses possessed moderate awareness about AI technology while harboring concerns about its implications (Alruwaili et al., 2024).”
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“For measuring nurses’ attitudes toward AI, the GAAIS was the most frequently used tool applied in 10 studies [15, 22, 37, 39, 41–43, 45, 50, 51] which primarily assesses nurses’ trust in AI, willingness to accept and use AI, as well as their positive and negative psychological and behavioral…”
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“…acknowledge AI's potential to improve clinical outcomes, increase workflow efficiency and reduce administrative tasks, frequently regarding AI as a tool that supports patient-centred care (Sandanasamy et al. 2025; Alruwaili et al. 2024; Salem et al. 2024; Kaplan and Uçar 2025; Wang et al. 2024).”
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“On the other hand, a nurse with poor emotion regulation skills may perceive AI as a threat and develop a negative attitude [26, 27].”
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“In general, younger nurses were found to have more positive attitudes toward technology compared to older nurses [14, 26].”
InfluentialValidation of the Short General Attitudes Towards Artificial Intelligence Scale: The Short GAAIS-10
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“This result aligns with previous studies reporting limited awareness and insufficient training among nurses (Alruwaili et al. 2024; Tuncer and Tuncer 2024).”
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“Similar to the fi ndings reported by Alruwaili et al. (15), an inverse relationship was observed between nurses ’ age and attitudes toward AI, with younger nurses demonstrating signi fi cantly more positive attitudes than older nurses (15).”
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“This aligns with findings of a study on exploring nurses' awareness and attitudes toward artificial intelligence: implications for nursing practice, which reported that nurses appreciate AI for reducing human error in nursing practices [17].”
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“Similarly, Alruwaili et al. 31 found that reluctance to change was inversely associated with positive AI perceptions.”
ATEŞ, A. Y., & ÇETİN, G. (2026) · Public Health Nursing · doi:10.1111/phn.70080 · Cited by 5
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“7,8 Studies consistently show that educational interventions significantly improve both AI knowledge and attitudes among nurses, with younger and more educated professionals demonstrating greater receptivity to AI adoption.”
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“For example, a recent study reported significant associations between nurses’ demographic characteristics such as age, gender, years of experience, and educational level and their attitudes toward artificial intelligence [24].”
Wei, T., Wang, T., Ruan, J., Pang, X., Zhou, P., Wang, Z., Hu, M., Chen, S., Zhang, X., & Li, C. (2026) · BMC Nursing · doi:10.1186/s12912-026-04920-5 · Cited by 3
“Notably, such attitudinal differences are not incidental but are shaped by a combination of social and psychological factors, among which generational differences are considered a key variable that cannot be overlooked [13].”
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“The increasing integration of artificial intelligence (AI)-based technologies into clinical practice not only requires nurses to work with new tools but also affects their perceptions of these technologies, their assessments of their competence, and their adaptation processes to change [3].”
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“…of Nurses, emphasize strengthening nurses’ digital competencies and AI-related education [10,11], as well as establishing ethical frameworks for AI [12], the successful and safe implementation of AI ultimately depends on how clinical nurses perceive, prepare for, and engage with these technologies…”
Awad, W. H. A., Awad, N. H. A., Ashour, H. M. A. A., Khamis, E., Yassen, M., Ismail, H. I. A. B., Syam, N. M., & Hashem, E. S. (2026) · International Journal of Nursing Studies Advances · doi:10.1016/j.ijnsa.2026.100577 · Cited by 2
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“As Alruwaili et al. [51] noted, the integration of new technologies requires both technical preparedness and the psychological confidence to navigate professional challenges.”
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Aljamaan, F., Mubarak, M., Altamimi, I., Alanteet, A. A., Alsalman, M., Dasuqi, S. A., Alballaa, R., Alarifi, M. I., Saadon, A. A., Alhaqbani, A. O., et al. (2025) · Research Square · doi:10.21203/rs.3.rs-6222830/v1
HEMŞİRELİK ÖĞRENCİLERİNİN YAPAY ZEKAYA YÖNELİK GENEL TUTUMLARI VE ETKİLEYEN FAKTÖRLER
Yazıcı, H. G., Ökten, Ç., & Akdulum, G. H. (2025) · Sağlık Bilimleri Dergisi · doi:10.34108/eujhs.1541870
Investigation of Surgical Nurses' Anxiety and General Attitudes Towards Artificial Intelligence
Guneş, H., Okutan, Ş., Dolanbay, N., & Bostancı, M. E. (2025) · Journal of Basic and Clinical Health Sciences · doi:10.30621/jbachs.1721430 · Cited by 1
Educational, Technological, Epistemic, and Pedagogical Architectures for an Ageing World
Alam, A. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5462-0.ch010
Infection Control and Artificial Intelligence—AI
Gašpert, T. (2025) · Principles of specialty nursing · doi:10.1007/978-3-032-01446-7_8
Ethical Considerations in AI Integration
McLeod‐Sordjan, R. (2026) · Springer eBooks · doi:10.1007/978-3-032-12402-9_3
Ali, M. A., & Abdallah, I. E. (2026) · Research Square · doi:10.21203/rs.3.rs-8063905/v1
Triveni, B., Dadhabai, S., & Kumar, B. P. (2026) · Journal of Education and Health Promotion · doi:10.4103/jehp.jehp_639_25
Artificial Intelligence in the Nursing Profession: Applications, Challenges, and Future Directions
Philip, R. (2026) · International Journal of Medical Pharmaceutical and Health Sciences (IJMPHS). · doi:10.62946/ijmphs/3.1.473-485 · Cited by 1
“%) of the participants in a recent Saudi Arabian study had any practical knowledge of AI-integrated technology, while nurses' knowledge of AI was relatively minimal [86] .”
Ahmed, A. K., Chandio, I. A., Khan, I. M., Kumar, P. R., Bahadur, R., & Malhi, S. D. (2026) · NURSEARCHER (Journal of Nursing & Midwifery Sciences) · doi:10.54393/nrs.v6i1.225
Attitudes Toward Artificial Intelligence and E-Health Literacy: A Study Among Nurses
Akçoban, S., Tüzmen, H. D., & YÜKSEL, H. (2026) · Acibadem Universitesi Saglik Bilimleri Dergisi · doi:10.31067/acusaglik.1840596
Generative Artificial Intelligence for Enhancing Nursing Educators’ Awareness and Attitudes
Majima, T., Higashitsuji, A., Otsuka, T., Mori, T., Yokota, S., Yamasaki, Y., Ishii, A., Chien, S. C., & Wazumi, Y. (2026) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000001531
Zeng, Q., Zhu, J., Yang, C. R., Hu, J., & Huang, X. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1786184
“However, most previous studies (4, 5, 10) have predominantly relied on calculating total scores from traditional instruments, such as literacy scales or attitude scales, and utilized mean comparisons or descriptive statistics to examine the current state of nurses’ AI perceptions.”
Mitsuhashi, T. (2026) · Cureus · doi:10.7759/cureus.110118
“Evidence from studies on AI-related attitudes and readiness indicates that professional context, digital competence, and perceived usefulness are associated with the intention to adopt AI tools and that patterns can differ between healthcare workers and patients or the general public [6-8].”
Fan, X., Sun, J., Zhang, L., Wang, J., Dong, B., Gao, X., Jin, R., & Huai, P. (2026) · JMIR Nursing · doi:10.2196/90253
“This confidence in specific technical domains serves as the intrinsic motivation driving health care professionals to actively engage with, deeply explore, and persistently use AI tools [22].”
Li, X. J., Jing, C., Gong, Z., Zhang, J., & Zhang, S. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1842497
“Studies consistently reveal weak foundational AI literacy, low practical adoption rates, and a notable knowledge – practice gap among nurses (82).”
Betkus, M. H., Banner, D., Currie, L. M., Jackson, P. J., & Freeman, S. (2026) · Canadian Journal of Nursing Research · doi:10.1177/08445621261463882
“The studies included nurses (Alruwaili et al., 2024; Swan, 2021), nursing students (Kwak et al., 2022), radiologists (Botwe et al., 2021; Coakley et al., 2022), physicians (Oh et al., 2019), medical students (Mehta et al., 2021), healthcare professionals inclusive of nurses (Abdullah & Fakieh,…”
InfluentialTorreno, F., & FLORES, F. (2026) · Research Square · doi:10.21203/rs.3.rs-10357554/v1
Ghazali, M. N. A., & Riaz, M. A. (2026) · BMJ Open · doi:10.1136/bmjopen-2026-121820
Knowledge, attitude, and awareness of artificial intelligence among medical staff in Kabul City
Rahimi, A. M., Bashari, A. B., Mohammadi, M. A., Rahimi, M. T., Paiwand, M. N., Hussiani, S., Qurbani, M. R., & Mohammadi, A. (2026) · Annals of Medicine and Surgery · doi:10.1097/ms9.0000000000005363
“Continuous and structured education of health workers about artificial intelligence will increase their awareness and enable them to use it effectively in their daily professional work [16] .”
Aljamaan, F., Mubarak, M. F., Altamimi, I., Alanteet, A. A., Alsalman, M. A., Dasuqi, S. A., Alballaa, R., Alarifi, M. I., Saadon, A. A., Alhaqbani, A. O., et al. (2026) · Health Science Reports · doi:10.1002/hsr2.72904
Balachandran, S., Muliira, J. K., Lazarus, E. R., Bulushi, S. A. J. A., Mamari, R. A., Bakri, A. N. A., & Alawi, S. A. (2026) · Sci · doi:10.3390/sci8080194
“A cross-sectional approach was chosen to provide a snapshot of nurses’ AI literacy and fear towards AI in the country and this helped to explore associations between these two constructs without inferring causality [19,20].”
Albarqi, M. N. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1843244
“Key facilitators include supportive leadership, availability of technical infrastructure, integration with existing clinical workflows, and stakeholder engagement throughout the implementation process (4).”
David-Olawade, A. C., Osonuga, A. A., & Olawade, D. B. (2026) · Applied Nursing Research · doi:10.1016/j.apnr.2026.152135
Informatics Techniques in Nursing Course and Readiness for Medical Artificial Intelligence
Özden, G., Aktura, S. Ç., Ceviz, A., & Ceviz, R. (2026) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000001611
Metadata
- Authors
- Alruwaili, M. M., Abuadas, F. H., Alsadi, M., Alruwaili, A. N., Elsayed Ramadan, O. M., Shaban, M., Al Thobaity, A., Alkahtani, S. M., & El Arab, R. A.
- Affiliations
- Jouf University (SA)
- Department of Maternity and Pediatric Health Nursing, College of Nursing, Jouf University, Sakaka, Saudi Arabia
- Department of Medical Surgical Nursing, Nursing College, Taif University, Taif, Saudi Arabia
- Ministry of Health (SA)
- Department of Health Management and Informatics, AL Moosa College of Health Sciences, Al Ahsa, Saudi Arabia
- Corresponding author
- Abuadas, Fuad H.
- ORCID
- Venue
- DIGITAL HEALTH
- Publisher
- SAGE Publications
- Published
- 2024-01
- Volume
- 10
- Pages
- 20552076241271803-20552076241271803
- ISSN
- 2055-2076 (ISSN-L)
- PMC
- PMC11304479
- OpenAlex
- W4401376712
- Semantic Scholar
- 5b48a702de8601632522c13bbcf5b7e732018d3e
- Cited by
- 114
- References
- 27
- Citations by year
- 2026: 59 · 2025: 47 · 2024: 8
- FWCI
- 10.68
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Digital Health (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Al Jouf University (Deanship of Scientific Research at Jouf University)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- artificial intelligence in healthcare, nurses' attitudes, nurses' awareness, AI knowledge, gender differences, age differences, educational attainment, generational differences, clinical implementation of AI, change management, nursing workforce
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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