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.
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.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
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Claims the paper makes
0 of 24 cited sources checked · 0 supported · 0 flagged
- Findingown data
Nurses displayed moderate levels of awareness toward AI technology.
“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.”
Quote in the paperSubstantial claim - Findingown data
Nurses expressed openness to AI integration (M = 3.51).
“Nurses expressed openness to AI integration (M = 3.51) on one side, but also had some concerns about AI.”
Quote in the paperSubstantial claim - Findingown data
45.5% of nurses reported that they had used AI to calculate drug doses.
“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.”
Quote in the paperNot a substantial claim - Findingown data
The mean score for the item "I would like to use AI in my job" was 3.50 (SD = 0.99).
“the mean score for the item “I would like to use AI in my job” was 3.50 (SD = 0.99)”
Quote in the paperSubstantial claim - Findingown data
Female nurses exhibited a higher proportion of negative attitudes compared to male nurses.
“Female nurses exhibited a higher proportion of negative attitudes compared to male nurses.”
Quote in the paperNot a substantial claim
- Findingcitation
Just above half (58.2%) of the participating nurses demonstrated practical knowledge of AI-integrated technology.
“Just above half (58.2%) of the participating nurses demonstrated practical knowledge of AI-integrated technology.4,5,13”
Quote in the paperSubstantial claim - Findingown data
Nurses had some concerns about AI.
“Nurses expressed openness to AI integration (M = 3.51) on one side, but also had some concerns about AI.”
Quote in the paperNot a substantial claim - Findingown data
40.0% of nurses reported encountering AI in nursing diagnosis through electronic care systems.
“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.”
Quote in the paperNot a substantial claim - Findingown data
39.1% of nurses reported that the basics of AI were covered in their undergraduate education.
“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.”
Quote in the paperNot a substantial claim - Findingown data
60.0% of nurses reported knowledge about AI-integrated applications.
“Concerning AI-integrated applications, 60.0% of nurses reported knowledge about it, while 40.0% indicated a lack of knowledge.”
Quote in the paperNot a substantial claim - Findingown data
58.2% (128 nurses) were considered aware of AI as they dealt with one of its healthcare applications.
“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.”
- Also stated in: § Nurses’ awareness toward AI · plain
“Additionally, 58.2% of nurses reported encountering and using AI means in the medical field, whereas 41.8% had not.”
Quote in the paperSubstantial claim - Also stated in: § Nurses’ awareness toward AI · plain
- Findingown data
Younger nurses demonstrated more positive attitudes toward AI compared to older 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.”
Quote in the paperNot a substantial claim - Findingown data
A considerable proportion of nurses hold conservative attitudes toward AI, ranging from mild caution to significant resistance against integration of AI technologies in nursing practices.
“The analysis revealed that nurses’ attitudes toward AI can be described as conservative, with the mean scores indicating a general hesitancy to feel comfortable with AI-integrated technologies.”
- Also stated in: § Discussion · hedged
“The findings of this study indicate that a considerable proportion of nurses hold conservative attitudes toward AI, which encompasses a spectrum of hesitancy from mild caution to significant resistance against the integration of AI technologies in nursing practices.7,12”
Quote in the paperSubstantial claim - Also stated in: § Discussion · hedged
- Findingown data
No significant variations in attitudes toward AI were found based on years of nursing experience (χ2 = 2.67, p = 0.61).
“no significant variations in attitudes toward AI were found based on years of nursing experience (χ² = 2.67, p = 0.61).”
Quote in the paperNot a substantial claim - Findingown data
There was a significant difference in attitudes toward AI based on age (χ2 = 9.31, p < 0.05).
“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.”
Quote in the paperNot a substantial claim - Findingown data
The mean score for the item "AI systems can perform better than humans" was 2.99 (SD = 1.07).
“the item “AI systems can perform better than humans” scored lower at 2.99 (SD = 1.07)”
Quote in the paperSubstantial claim - Findingown data
Years of nursing experience did not reveal significant variations in attitudes toward AI.
“However, years of nursing experience did not reveal significant variations in attitudes.”
Quote in the paperNot a substantial claim - Findingown data
There was a significant difference in attitudes toward AI based on educational background (χ2 = 6.70, p < 0.05).
“Educational background yields significant differences (χ² = 6.70, p < 0.05), with nurses holding undergraduate degrees exhibiting the highest positive attitudes.”
Quote in the paperNot a substantial claim - Findingown data
Nurses holding undergraduate degrees exhibited the highest positive attitudes toward AI.
“Educational background yields significant differences (χ² = 6.70, p < 0.05), with nurses holding undergraduate degrees exhibiting the highest positive attitudes.”
Quote in the paperNot a substantial claim - Findingown data
70.9% of nurses had basic information about AI.
“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.”
- Also stated in: § Nurses’ awareness toward AI · plain
“For the definition of AI, 70.9% of nurses indicated having basic information, while 29.1% reported not having such knowledge.”
Quote in the paperNot a substantial claim - Also stated in: § Nurses’ awareness toward AI · plain
- Findingown data
The current study revealed only a moderate level of awareness toward AI among practicing nurses.
“Despite the opportunities afforded by AI, the results of the current study revealed only a “moderate” level of awareness toward AI among practicing nurses.”
Quote in the paperSubstantial claim - Findingown data
Nurses expressed conservative attitudes toward AI.
“Nurses expressed conservative attitudes toward AI, with significant differences observed based on gender (χ² = 4.67, p < 0.05).”
Quote in the paperSubstantial claim - Findingown data
No significant differences were observed in attitudes toward AI between single/divorced (20%) and married nurses (26.4%) (χ2 = 0.14, p = 0.71).
“no significant differences were observed in attitudes toward AI between single/divorced (20%) and married nurses (26.4%) (χ² = 0.14, p = 0.71).”
Quote in the paperNot a substantial claim - Findingown data
67.3% of nurses acknowledged being aware of the use of AI in the medical field.
“A substantial majority (67.3%) acknowledged being aware of the use of AI in the medical field, with 32.7% indicating no familiarity with AI applications.”
Quote in the paperNot a substantial claim - Findingown data
Nurses have concerns that AI tools may transform the traditional nursing role and take over or control nursing functions.
“Nurses have concerns that the application of different AI tools in nursing practice may result in a major transformation of the traditional nursing role in healthcare settings.”
- Also stated in: § Conclusions · hedged
“This increased the Saudi nurses’ anxiety and concerns toward AI technology which may take over or control the nursing functions.”
Quote in the paperSubstantial claim - Also stated in: § Conclusions · hedged
- Premisecitation
Despite significant advancements, AI tools have not been effectively utilized or promoted since their inception several years ago.
“Despite significant advancements, these valuable tools have not been effectively utilized or promoted since their inception several years ago.19,20”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [19] Risling T. Educating the nurses of 2025: technology trends of the next decade. Nurse Educ Pract 2017; 22: 89– 92. 28049072 source
Not checked in the free run.
- cites [20] Nagle LM Kleib M Furlong K. Digital health in Canadian schools of nursing part A: nurse educators’ perspectives. Qual Adv-Avancées en formation infirmière 2020; 6: 4.
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- Premisecitation
Younger nurses tend to hold more positive attitudes toward technology in general compared to elder nurses.
“Younger nurses tend to hold more positive attitudes toward technology in general compared to elder nurses. 29”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [29] Bozak MG. Using Lewin’s force field analysis in implementing a nursing information system. Comput Inform Nurs 2003; 21: 80– 85. 12802948 source
Not checked in the free run.
- Premisecitation
Many gaps still exist where nurses are not yet involved in the process of developing, integrating, and implementing AI in healthcare.
“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”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [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 source
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- Interpretationcitation
The current study's results on conservative attitudes and concerns toward AI are contrary to Kwak et al.'s finding of positive willingness among student nurses to work with AI-integrated applications.
“The current study results about the conservative attitudes and concerns toward AI technology come in contrary to the results reported by Kwak et al., 31 as they examined the attitudes of student nurses toward AI technology and resulted in the positive willingness of the students to work with AI-integrated applications in nursing practice with ease.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [31] Kwak Y Ahn J-W Seo YH. Influence of AI ethics awareness, attitude, anxiety, and self-efficacy on nursing students’ behavioral intentions. BMC Nurs 2022; 21: 1– 8. 36180902 PMC9526272 source
Not checked in the free run.
- Study design and conductcitation
The Nurses' AI knowledge questionnaire had internal consistency with Cronbach's alpha of 0.795, as reported by Swed et al.
“The tool's internal consistency of the used sub-scales was shown by Cronbach's alpha values of 0.795, as reported by Swed et al. 22”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [22] Swed S Alibrahim H Elkalagi NKH, et al. Knowledge, attitude, and practice of artificial intelligence among doctors and medical students in Syria: a cross-sectional online survey. Front Artif Intell 2022; 5: 1011524. 36248622 PMC9558737 source
Not checked in the free run.
- Interpretationreasoning
The difference between the current study's results and Kwak et al.'s results can be related to generational differences among nurses.
“These results can be related to the generational differences among nurses. 30”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [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
Not checked in the free run.
- Interpretationown data
The mean scores suggest a cautious approach to fully endorsing AI-integrated tools in clinical practice.
“These scores suggest a cautious approach to fully endorsing AI-integrated tools in clinical practice.”
Quote in the paperSubstantial claim - Premisecitation
Improper introduction of AI technology may lead to stress, anxiety, and the development of negative attitudes among nurses toward such technology.
“It may lead to stress, anxiety, and the development of negative attitudes among nurses toward such technology if it is not properly introduced.12,15,18”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [12] Clancy TR. Artificial intelligence and nursing: the future is now. J Nurs Adm 2020; 50: 125– 127. 32068622 source
Not checked in the free run.
- cites [15] Robert N. How artificial intelligence is changing nursing. Nurs Manage 2019; 50: 30– 39. PMC7597764 31425440 source
Not checked in the free run.
- cites [18] Haleem A Javaid M Singh RP, et al. Medical 4.0 technologies for healthcare: features, capabilities, and applications. Internet Things Cyber-Phys Syst 2022; 2: 12– 30. source
Not checked in the free run.
- May combine two claims. 12
- The quote only partly states this claim. 1
- Classified as probably not a substantial claim. 6
May combine two claims.
Findingown dataNurses 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).
“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).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataNurses 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).
“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).”
Quote in the paperNot a substantial claimThe quote only partly states this claim.
Findingown dataThere was a significant difference in attitudes toward AI based on gender (χ2 = 4.67, p < 0.05).
“Nurses expressed conservative attitudes toward AI, with significant differences observed based on gender (χ² = 4.67, p < 0.05).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataA 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).
“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).”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductcitationThe GAAIS exhibited good convergent and divergent validity with a related scale.
“Additionally, the GAAIS exhibited good convergent and divergent validity with a related scale.23,24”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [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 in the free run.
- cites [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
Not checked in the free run.
May combine two claims.
Study design and conductcitationThe 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.
“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”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [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
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAI could help solve some of the problems facing the nursing profession, such as job dissatisfaction and unintended deficiencies in patient care.
“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”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [15] Robert N. How artificial intelligence is changing nursing. Nurs Manage 2019; 50: 30– 39. PMC7597764 31425440 source
Not checked in the free run.
- cites [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
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenMissing data were handled by excluding cases with incomplete responses from the analysis.
“Missing data were handled by excluding cases with incomplete responses from the analysis.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataFemale nurses and nurses older than 50 years demonstrated more conservative attitudes toward AI than their counterparts.
“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.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe study obtained approval from the Bioethics Institutional Review Board at Jouf University (Approval no. 3-06-44, 7 February 2023).
“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”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataA total of 220 nurses participated in the study, providing complete responses, exceeding the anticipated recruitment target.
“However, a total of 220 nurses participated in the study, providing complete responses to the questionnaire, exceeding the anticipated recruitment target.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationConservative 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.
“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”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [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 in the free run.
- cites [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 in the free run.
May combine two claims.
PremisecitationNurses who have positive views and attitudes toward AI are more likely to feel comfortable using AI applications and view AI and other technology applications as useful and easy to use.
“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”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [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 in the free run.
- cites [29] Bozak MG. Using Lewin’s force field analysis in implementing a nursing information system. Comput Inform Nurs 2003; 21: 80– 85. 12802948 source
Not checked in the free run.
May combine two claims.
Interpretationown dataDemographic factors play a crucial role in shaping perceptions of technological advancements, as conservative attitudes are particularly pronounced among female and older nurses.
“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”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [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 in the free run.
- cites [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 in the free run.
- cites [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
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationcitationThe conservative attitudes can be explained by nurses' thoughts about changes to their role in practice settings as AI-integrated technology may affect the decision-making process and lead nurses and other healthcare practitioners.
“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”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [12] Clancy TR. Artificial intelligence and nursing: the future is now. J Nurs Adm 2020; 50: 125– 127. 32068622 source
Not checked in the free run.
May combine two claims.
PremisecitationThe changing role of nurses may introduce anxiety toward AI, which directly affects attitudes toward AI and potential difficulties in future adoption and usage, in addition to concern of invaded privacy from AI-integrated technology applications.
“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”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [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
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
Study design and conductreasoningThe study results are limited to nursing professionals in a specific setting and are cross-sectional, so caution should be practiced in generalization.
“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.”
Quote in the paperSubstantial claim
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.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
One descriptive study assessing nurses' awareness and attitudes toward AI in clinical practice met four MMAT criteria due to a limited sample drawn from three hospitals.
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Participants with less than one year of experience appear despite eligibility rule
MajorThe inclusion criterion requires at least one year of clinical experience, but Table 1 lists 28 participants with less than one year of nursing experience.
“The inclusion criteria for participants involved registered nurses in Saudi Arabia with at least one year of clinical experience”
“| Years of nursing experience | <1 year | 28 | 12.7 |”
Attitude totals differ across demographic analyses
MajorTable 4 classifies the same 220 nurses as 114 negative and 106 positive by gender, but as 90 negative and 130 positive by age. These totals cannot both describe the same participants, undermining the reported comparisons of attitudes.
“| 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 |”
“| 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 |”
A 45% group is described as over half
MinorThe reported 45% with at least a decade of experience is less than half, contrary to the description.
“over half of the participants”
“(45%) had a decade or more of experience”
Collection period is called four months but spans April through September
MinorApril through September spans six calendar months, not four.
“The data was collected over four months”
“(April to September 2023)”
Single nurses' percentage does not match the count
MinorTable 1 reports 84 single nurses out of 220 as 37.3%; the count corresponds to 38.2% when rounded to one decimal place. The separated/divorced/widowed count of 8 is likewise 3.6%, not the reported 4.5%.
Reported 37.3 · recomputed 38.181818
“| Marital status | Single | 84 | 37.3 |”
Cites
1 retracted
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“11 The practice of nursing was signi fi cantly affected in the last decade by the introduction of AI.”
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“14 Nurses ’ experiences with AI in terms of competence, understanding, reliability, and con fi dence in its potential as an alternative to human interventions in healthcare vary.”
BackgroundInitial validation of the general attitudes towards Artificial Intelligence Scale
Schepman, A., & Rodway, P. (2020) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2020.100014 · Cited by 785 · cited 2× · see citing works
“23 It is a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree).”
BackgroundUse of AI-based tools for healthcare purposes: a survey study from consumers’ perspectives
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“12 The changing role of nurses may introduce anxiety toward AI, 27 which directly affects the attitudes toward AI and the resulting potential dif fi culties 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 appli…”
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“24 Additionally, the GAAIS exhibited good convergent and divergent validity with a related scale.”
BackgroundMedical 4.0 technologies for healthcare: Features, capabilities, and applications
Haleem, A., Javaid, M., Pratap Singh, R., & Suman, R. (2022) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2022.04.001 · Cited by 468 · cited 2× · see citing works
“12,15,18 To integrate AI effectively into nursing education, nursing educators must assess the training needs speci fi c to this endeavor.”
BackgroundRonquillo, C. E., Peltonen, L., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., Cato, K., Hardiker, N., Junger, A., Michalowski, M., et al. (2021) · Journal of Advanced Nursing · doi:10.1111/jan.14855 · Cited by 453 · cited 2× · see citing works
“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.”
BackgroundArtificial intelligence in nursing and midwifery: A systematic review
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“7,26 Ensuring that AI tools are introduced with adequate support and training, and are aligned with nurses ’ professional values and ethics, will be essential in overcoming resistance and integrating these technologies successfully.”
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“12,15,18 To integrate AI effectively into nursing education, nursing educators must assess the training needs speci fi c to this endeavor.”
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“…current study results about the conservative attitudes and concerns toward AI technology come in contrary to the results reported by Kwak et al., 31 as they examined the attitudes of student nurses toward AI technology and resulted in the positive willingness of the students to work with…”
ResultEthical Principles for Medical Research Involving Human Subjects
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“25 To ensure con fi dentiality and anonymity, various measures were implemented, including assigning a distinct code number to each participating nurse and presenting all data in aggregated form.”
MethodPark, J., & Woo, S. E. (2022) · The Journal of Psychology · doi:10.1080/00223980.2021.2012109 · Cited by 243 · see citing works
Swed, S., Alibrahim, H., Elkalagi, N. K. H., Nasif, M. N., Rais, M. A., Nashwan, A. J., Aljabali, A., Elsayed, M., Sawaf, B., Albuni, M. K., et al. (2022) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2022.1011524 · Cited by 185 · cited 2× · see citing works
“The tool ’ s internal consistency of the used sub-scales was shown by Cronbach ’ s alpha values of 0.795, as reported by Swed et al. 22 This section consists of seven items measured as “ Yes or No ” questions to assess the level of nurses ’ awareness of common terms of AI used in healthcare.”
BackgroundMethodInfluentialChallenges and policy opportunities in nursing in Saudi Arabia
Alluhidan, M., Tashkandi, N., Alblowi, F., Omer, T., Alghaith, T., Alghodaier, H., Alazemi, N., Tulenko, K., Herbst, C. H., Hamza, M. M., et al. (2020) · Human Resources for Health · doi:10.1186/s12960-020-00535-2 · Cited by 184 · cited 1× · see citing works
“15,17 However, this may cause concerns among nurses, especially when it comes to incorporating new technologies into practice.”
BackgroundIntegration of artificial intelligence into nursing practice
Abuzaid, M. M., Elshami, W., & Fadden, S. M. (2022) · Health and Technology · doi:10.1007/s12553-022-00697-0 · Cited by 172 · see citing works
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“7,19 AI technologies, with their related products of predictive analytics, natural language processing, computer vision, and machine learning, may enable the extraction of actionable insights from data, enhancing clinical work fl ows, diagnostic accuracy, and treatment recommendations.”
BackgroundArtificial Intelligence and Nursing: The Future Is Now
Clancy, T. R. (2020) · JONA: The Journal of Nursing Administration · doi:10.1097/nna.0000000000000855 · Cited by 103 · cited 6× · see citing works
“12,15,18 To integrate AI effectively into nursing education, nursing educators must assess the training needs speci fi c to this endeavor.”
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BOZAK, M. G. (2003) · CIN: Computers, Informatics, Nursing · doi:10.1097/00024665-200303000-00008 · Cited by 89 · cited 2× · see citing works
“28,29 The fi ndings of this study indicate that a considerable proportion of nurses hold conservative attitudes toward AI, which encompasses a spectrum of hesitancy from mild caution to signi fi cant resistance against the integration of AI technologies in nursing practices.”
BackgroundHwang, G.-J., Tang, K.-Y., & Tu, Y.-F. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2022.2086579 · Cited by 87 · cited 3× · see citing works
“7,26,30 The current study results about the conservative attitudes and concerns toward AI technology come in contrary to the results reported by Kwak et al., 31 as they examined the attitudes of student nurses toward AI technology and resulted in the positive willingness of the students to work…”
BackgroundResultHandbook of Artificial Intelligence in Healthcare
(2021) · Intelligent systems reference library · doi:10.1007/978-3-030-83620-7 · Cited by 24 · see citing works
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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.”
BackgroundHealth sector transformation program 2030 in Saudi Arabia and implications in dentistry
Soman, C. (2022) · Saudi Journal of Oral Sciences · doi:10.4103/sjoralsci.sjoralsci_21_22 · Cited by 4 · see citing works
Flagged first, then by citations
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- WHO, 2016, Working for health and growth: Investing in the health workforce
- Nagle LM, 2020, Qual Adv-Avancées en formation infirmière, 6, 4
- Alhashmi S, 2019, Int J Inf Technol Lang Stud, 3, 27
Cited by
Sorted by citations
Tun, H. M., Rahman, H. A., Naing, L., & Malik, O. A. (2025) · Journal of Medical Internet Research · doi:10.2196/69678 · Cited by 210 · see citing works
“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
El Arab, R. A., Al Moosa, O. A., Abuadas, F. H., & Somerville, J. (2025) · Journal of Medical Internet Research · doi:10.2196/69881 · Cited by 160 · see citing works
“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 · see citing works
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 · see citing works
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 131 · see citing works
Dailah, H. G., Koriri, M. D., Sabei, A., Kriry, T., & Zakri, M. (2024) · Healthcare · doi:10.3390/healthcare12242555 · Cited by 106 · see citing works
“%) of the participants had any practical knowledge of AI-integrated technology [146].”
Arab, R. A. E., Moosa, O. A. A., Sagbakken, M., Ghannam, A., Abuadas, F. H. A., Somerville, J. G., & Mutair, A. S. A. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1619378 · Cited by 119 · see citing works
Self-citationEl-Banna, M. M., Sajid, M. R., Rizvi, M. R., Sami, W., & McNelis, A. M. (2025) · Frontiers in Medicine · doi:10.3389/fmed.2025.1681784 · Cited by 62 · see citing works
Almagharbeh, W. T., Alfanash, H. A., Alnawafleh, K. A., Alasmari, A. A., Alsaraireh, F. A., Dreidi, M. M., & Nashwan, A. J. (2025) · BMC Nursing · doi:10.1186/s12912-024-02658-6 · Cited by 74 · see citing works
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 · see citing works
“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 · see citing works
“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].”
InfluentialThe role of artificial intelligence in enhancing nurses' work-life balance
Rony, M. K. K., Alrazeeni, D. M., Akter, F., Nesa, L., Das, D. C., Uddin, M. J., Begum, J., Khatun, M. T., Noor, M. A., Ahmad, S., et al. (2024) · Journal of Medicine Surgery and Public Health · doi:10.1016/j.glmedi.2024.100135 · Cited by 45 · see citing works
Rony, M. K. K., Ahmad, S., Das, D. C., Tanha, S. M., Deb, T. R., Akter, M. R., Khatun, M. A., Khalil, M. I., Peu, U. R., Parvin, M. R., et al. (2025) · Health Science Reports · doi:10.1002/hsr2.70728 · Cited by 38 · see citing works
Are nurses and patients willing to work with service robots in healthcare? A mixed-methods study
El‐Gazar, H. E., Abdelhafez, S., Ali, A. M., Shawer, M., Alharbi, T. A. F., & Zoromba, M. A. (2024) · BMC Nursing · doi:10.1186/s12912-024-02336-7 · Cited by 35 · see citing works
“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
Areshtanab, H. N., Rahmani, F., Vahidi, M., Saadati, S. Z., & Pourmahmood, A. (2025) · Scientific Reports · doi:10.1038/s41598-025-11002-0 · Cited by 37 · see citing works
“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 · see citing works
Gundlack, J., Negash, S., Thiel, C., Buch, C., Schildmann, J., Unverzagt, S., Mikolajczyk, R., & Frese, T. (2025) · Health Expectations · doi:10.1111/hex.70216 · Cited by 27 · see citing works
Transforming Nursing Education with Artificial Intelligence: A Systematic Review (2010–2025)
Alrazeeni, D. M., Alharrasi, M., Rony, M. K. K., Biswas, R. K., Tama, I. J., Halder, C. R., Deb, B., Bashar, F., & Akter, F. (2026) · SAGE Open Nursing · doi:10.1177/23779608261424597 · Cited by 36 · see citing works
“Educators also expressed concern over feedback generated by AI systems that sometimes contradict human instructors or appear imper-sonal (Alruwaili et al., 2024; Weidener & Fischer, 2024).”
Dai, Q., Li, M., Shi, S., Yang, M., Wang, Z., Liao, J., Li, Z., Liu, J., Deng, J. J., & Tao, L. (2025) · BMC Nursing · doi:10.1186/s12912-025-03748-9 · Cited by 25 · see citing works
“Among 220 registered nurses in Saudi Arabia, 70.9% demonstrated foundational AI knowledge, albeit with tempered optimism [55].”
Influential(2025) · doi:10.1016/j.ijnss.2025.04.009 · Cited by 24 · see citing works
Baraka, A. A. E., Alhijji, M. A. A., Alrajeh, R. A. I., Alotaibi, D. N. B., Bukhamis, S., Alsafraa, N. A. M., & Hassan, E. A. (2025) · International Nursing Review · doi:10.1111/inr.70035 · Cited by 23 · see citing works
Chen, Y., Wu, F., Zhang, W., Xing, W., Zhu, Z., Huang, Q., & Yuan, C. (2025) · Nursing Reports · doi:10.3390/nursrep15060218 · Cited by 20 · see citing works
“In addition, Alruwaili et al. evaluated nurses’ awareness and attitudes toward AI tools in clinical settings [13].”
Elbassal, N. A. M. M., El‐Sayed, A. A. I., & Elgamal, H. G. (2025) · BMC Nursing · doi:10.1186/s12912-025-03896-y · Cited by 26 · see citing works
“Studies indicate that nurses who perceive AI positively are more likely to use it effectively, improve clinical accuracy, and enhance patient safety [11, 24].”
Alenazi, L., & Alhalal, E. (2025) · Nurse Education Today · doi:10.1016/j.nedt.2025.106780 · Cited by 17 · see citing works
Kang, R., Xuan, Z., Tong, L., Wang, Y., Jin, S., & Xiao, Q. (2025) · Journal of Medical Internet Research · doi:10.2196/65523 · Cited by 19 · see citing works
“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 · see citing works
“Similarly, research in Saudi Arabia revealed that nurses possessed moderate awareness about AI technology while harboring concerns about its implications (Alruwaili et al., 2024).”
Research on artificial intelligence literacy among nursing professionals: a scoping review
Wang, Q., Lu, N., Yu, C., Qi, J., Zhang, H., & Shi, H. (2026) · BMC Nursing · doi:10.1186/s12912-026-04448-8 · Cited by 16 · see citing works
“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…”
Nurses’ Intention to Integrate AI Into Their Practice: Survey Study in Canada
Paré, G., Raymond, L., & Sosso, F. A. E. (2025) · JMIR Nursing · doi:10.2196/76795 · Cited by 16 · see citing works
“Prior research suggests that favorable attitudes, such as high perceived usefulness and low anxiety, can promote AI adoption, whereas negative emotional responses may deter it [21-26].”
Bahari, G., Alenazi, L., & Alkathiri, A. M. (2025) · Nurse Education Today · doi:10.1016/j.nedt.2025.106816 · Cited by 10 · see citing works
Qutishat, M., & Shakman, L. (2025) · International Nursing Review · doi:10.1111/inr.70077 · Cited by 11 · see citing works
El‐Gazar, H. E., Shawer, M., Alenezi, A., Shaban, M., Zaky, M. E., & Zoromba, M. A. (2025) · Journal of Advanced Nursing · doi:10.1111/jan.16841 · Cited by 8 · see citing works
Self-citationLiu, X., Chen, Y., Guan, W., Jiang, P., Yan, L., Fan, M., & Zhou, Q. (2025) · Journal of Advanced Nursing · doi:10.1111/jan.70250 · Cited by 7 · see citing works
“…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).”
Raymond, L., Paré, G., Doyon, O., & Wagner, G. (2025) · Journal of Advanced Nursing · doi:10.1111/jan.70307 · Cited by 6 · see citing works
Influence of Attitude toward Artificial Intelligence (AI) on Job Performance with AI in Nurses
Morales-García, W. C., Sairitupa-Sanchez, L. Z., Paredes, A. F., Morales-García, M., & Gutierrez, F. N. (2025) · Data & Metadata · doi:10.56294/dm2025221 · Cited by 8 · see citing works
Artificial Intelligences Impact on Branding in Tourism
Gün, S. (2025) · Advances in marketing, customer relationship management, and e-services book series · doi:10.4018/979-8-3693-9461-8.ch007 · Cited by 6 · see citing works
Nurses’ Perspectives on AI in Clinical Practice
Lansdowne, M., Sperling, J. B., Lytle, K. S., Allen, D., Merrill, T., & Cary, M. P. (2025) · Nursing Administration Quarterly · doi:10.1097/naq.0000000000000710 · Cited by 6 · see citing works
Hacıalioğlu, N., Şeker, E. B., & Kaya, F. (2025) · BMC Psychology · doi:10.1186/s40359-025-03467-5 · Cited by 6 · see citing works
“On the other hand, a nurse with poor emotion regulation skills may perceive AI as a threat and develop a negative attitude [26, 27].”
Ali, S. I., & Shaban, M. (2026) · Nursing in Critical Care · doi:10.1111/nicc.70480 · Cited by 5 · see citing works
Self-citationÇOBAN, N., & Beydağ, K. D. (2025) · BMC Nursing · doi:10.1186/s12912-025-04248-6 · Cited by 4 · see citing works
“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
Schepman, A., & Rodway, P. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2610446 · Cited by 5 · see citing works
“The empirical evidence suggests that capturing AI attitudes that are deemed “general” has predictive value across a variety of contexts (e.g., Alruwaili et al., 2024; Bellaiche et al., 2023).”
Bashayreh, I., AlMekkawi, M., Omari, O. A., Melhem, O., Sinani, M. A., Maqbali, M. A. H. A., & ElKhalil, R. (2026) · Teaching and learning in nursing · doi:10.1016/j.teln.2025.12.022 · Cited by 4 · see citing works
Yıldırım, D., Yıldız, C. Ç., & Ergin, E. (2026) · Nursing and Health Sciences · doi:10.1111/nhs.70332 · Cited by 4 · see citing works
“This result aligns with previous studies reporting limited awareness and insufficient training among nurses (Alruwaili et al. 2024; Tuncer and Tuncer 2024).”
Alrazeeni, D. M., Alharrasi, M., Rony, M. K. K., Halder, C. R., Dhola, F.-T.-J., Aktery, A., & Tama, I. J. (2026) · Discover Public Health · doi:10.1186/s12982-026-01928-9 · Cited by 4 · see citing works
Alnazly, E. K., Absy, N., & Absy, N. (2026) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2026.1779382 · Cited by 4 · see citing works
“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).”
InfluentialJalal, S. M., Jalal, S. H., Alasmakh, K. E., Alnasser, Z., Alhamdan, W. Y., & Alabdullatif, A. A. (2025) · Cureus · doi:10.7759/cureus.82943 · Cited by 4 · see citing works
“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].”
Bıdık, N. Ü., & Turan, Z. (2025) · BMC Nursing · doi:10.1186/s12912-025-03346-9 · Cited by 8 · see citing works
Turan, M., & Cengi̇z, Z. (2025) · Nurse Education in Practice · doi:10.1016/j.nepr.2025.104574 · Cited by 4 · see citing works
Abuejheisheh, A. J., Haddad, R. H., Alafaghani, S., Thawabteh, A., Khanafseh, M., Sheebat, B., Horaini, L., Hawareen, B., Abughannam, Y., Dugan, C., et al. (2025) · Digital Health · doi:10.1177/20552076251393284 · Cited by 3 · see citing works
“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 · see citing works
“…attitudes toward AI are closely associated with educational background, prior experience, and perceived preparedness, underscoring the importance of systematically integrating AI-related competencies into health professions education (Alruwaili et al. 2024 ; Castagno and Khalifa 2020 ).”
Sayed, Z. A., Alnjadat, R. M., Khwaldeh, A., & Alqudah, L. M. M. (2026) · Nursing in Critical Care · doi:10.1111/nicc.70477 · Cited by 3 · see citing works
Mohamed, R. A., Alharbi, M. F. J., Aloufi, R., Abraham, N., Taref, N. N., Bauomy, E. S., Alkalash, S. H., Marzouk, M. M., & Almowafy, A. A. (2024) · PLoS ONE · doi:10.1371/journal.pone.0314206 · Cited by 3 · see citing works
Fayyad, M. B. N., Verbiest, J. R., Ivanova, A., Manto, M. U., & Moumdjian, L. (2024) · PLoS ONE · doi:10.1371/journal.pone.0315607 · Cited by 2 · see citing works
Majidpanah, K., Afra, A., & Tahery, N. (2025) · Journal of Nursing and Midwifery Sciences · doi:10.5812/jnms-165629 · Cited by 2 · see citing works
Nursing Educators’ Perceptions of AI in Research: Risks and Benefits
MRAYYAN, M. T., & Alomari, A. K. (2026) · Nursing Research and Practice · doi:10.1155/nrp/2058036 · Cited by 2 · see citing works
Rahman, R., Ahmed, H., Rony, M. K. K., Utsho, M. R., Kamal, M. B., Semi, M. A., Hossain, M., Das, S., & Rashid, M. M. (2026) · Nursing and Health Sciences · doi:10.1111/nhs.70321 · Cited by 2 · see citing works
“Similar findings have been reported in other contexts, where healthcare workers expressed fears of role displacement despite reassurances that AI functions as a supportive rather than sub-stitutive tool (Labrague et al. 2023; Alruwaili et al. 2024; Ibuki et al. 2024).”
Özden, B. A., & Duru, P. (2026) · Journal of Evaluation in Clinical Practice · doi:10.1111/jep.70421 · Cited by 2 · see citing works
Transforming Health Care AI Education Through Micro-learning
McCarthy, A., Agnew, J. D., Price, J., Strang, K., & McLaughlin, A. (2026) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000001535 · Cited by 2 · see citing works
“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.”
Elsayed, R. R. B., Nagy, A. M. E., Hussein, E. S. E., Elsayed, R. A. E., & Ramadan, R. M. E.-S. (2026) · BMC Nursing · doi:10.1186/s12912-026-04966-5 · Cited by 2 · see citing works
“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 · see citing works
“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].”
InfluentialAkay, G., SARUHAN, U., Saruhan, Y., Koç, E. S., & Oğuzhan, H. (2026) · BMC Nursing · doi:10.1186/s12912-026-05090-0 · Cited by 2 · see citing works
“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].”
Lin, X. Y., Qin, Y., Zhang, K., Zeng, Y., Zhu, X., Li, J., & Wang, Q. (2025) · Research Square · doi:10.21203/rs.3.rs-6836319/v1 · Cited by 2 · see citing works
Hemşirelerin Yapay Zekâ Kullanım Farkındalıklarının ve Etkileyen Faktörlerin Belirlenmesi
Nas, İ., Kahraman, H. A., Can, V., & Bulduk, M. (2025) · Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi · doi:10.37989/gumussagbil.1608194 · Cited by 2 · see citing works
Abiodun, A. O., Adeolu, O., Abayomi, B. D., & Julius, O. A. (2025) · doi:10.38124/ijisrt/25sep1438 · Cited by 1 · see citing works
Şener, Ş., GÜNGÖR, T., & Taşdelen, S. (2025) · Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi · doi:10.30783/nevsosbilen.1769627 · Cited by 2 · see citing works
Exploring the application of generative artificial intelligence in nursing: a cross-sectional study
Wu, J., Yang, M., Wei, X., Zheng, Y., & Deng, J. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1689418 · Cited by 1 · see citing works
Ge, X., Wang, H., Xu, Y., & Zhang, Y. (2026) · BMC Nursing · doi:10.1186/s12912-026-04433-1 · Cited by 1 · see citing works
Son, J.-E., & Park, Y. (2026) · Korean Journal of Adult Nursing · doi:10.7475/kjan.2026.0101 · Cited by 1 · see citing works
“…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 · see citing works
Huang, X., Niu, Q., Feng, Z., Shen, F., Yu, H., Yuan, X., Chen, X., & Xiao, F. (2026) · BMC Nursing · doi:10.1186/s12912-026-04842-2 · Cited by 1 · see citing works
“As Alruwaili et al. [51] noted, the integration of new technologies requires both technical preparedness and the psychological confidence to navigate professional challenges.”
Çakmak, V. S., & Yılmaz, C. (2026) · Journal of Evaluation in Clinical Practice · doi:10.1111/jep.70498 · Cited by 1 · see citing works
Garcia, P. R. B., Alhejaili, A. A., Muslihi, A., Alshahrani, B., Lamphon, H. T., Alhefnawy, K. A. H., Saleh, W., Natividad, M. J. B., Aljohani, M., & Fadlalmola, H. A. (2026) · International Journal of Nursing Studies Advances · doi:10.1016/j.ijnsa.2026.100636 · Cited by 1 · see citing works
Yingqi, D., Zhao, X., Pan, X., & Wei, J. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1880523 · Cited by 1 · see citing works
Tun, H. M., Rahman, H. A., Naing, L., & Malik, O. A. (2024) · doi:10.2196/preprints.69678 · Cited by 1 · see citing works
Paré, G., Raymond, L., & Sosso, F. A. E. (2025) · doi:10.2196/preprints.76795
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 · see citing works
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 · see citing works
“%) 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
- 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
- Social Sciences › Safety Research › 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
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