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Cited by 172Artificial Intelligence in Healthcare and EducationArtificial Intelligence ApplicationsNursing education and management

Integration of artificial intelligence into nursing practice

Open access
Abuzaid, Mohamed M, Elshami, Wiam, Fadden, Sonyia Mc·2022·Health and Technology
DOI 10.1007/s12553-022-00697-0PMC PMC9470236
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Abstract

Background: Artificial Intelligence (AI) is developing at a rapid pace and finding new applications across the health service team. Some professionals have voiced concerns over the implementation of AI, whilst others predict greater job opportunities in the future. Nursing practice will be directly affected and further information is required on the knowledge and perceptions of nurses regarding the integration of AI in practice. The study aims to assess the knowledge, attitude, willingness, and organizational readiness in integrating AI into nursing practice. Methods: An exploratory cross-sectional survey of nurses working in health organisations. A survey link was emailed to participants. Nurses working in the United Arab Emirates (UAE) health organisations were invited to participate. Eligibility criteria included registered nurses in government or private hospitals. The survey captured the nurses demographic, knoweldage, preceptions, orgianizational readinesss and challenges regarding implementation of AI into nursing practice. Results: 553 responses were returned from 650 invitation giving a response rate of 85%. 51% of respondents stated their knowledge on AI was obtained through self-taught measures for most of the participants, while 20% of them gained it through various courses. Only 8% stated they learned through postgraduate courses, while 9% stated they lack knowledge of AI. 75% of all respondents agreed that the nursing curriculum should include some basic knowledge of AI. Conclusions: There is a lack of understanding of the principles of AI across the nursing profession. Further education and training is required to enable a seamless and safe integration of AI into nursing practice.

AI snapshot

Written from the paper’s full text.

TL;DR

A cross-sectional survey of 553 nurses in the UAE found limited understanding of AI principles, with most AI knowledge self-taught. Nurses largely supported AI education and saw AI as important to nursing, but many also perceived threats to nursing practice or careers and reported unclear organizational readiness.

Key findings

  • Of 650 invited nurses, 553 responded (85%). Most obtained AI knowledge through self-taught measures (51%), while 20% gained it through courses, 8% through postgraduate courses, and 9% reported lacking AI knowledge; 75% agreed the nursing curriculum should include basic AI knowledge.
  • Knowledge was limited: 30% said their AI knowledge came only from news, posters, or media; 26% were familiar with AI but not confident applying it; 22% were comfortable with what it means; 12% were very comfortable working with AI applications; 10% did not understand it. Only 40% agreed they had a working knowledge of AI, while 69% agreed they had a basic understanding.
  • Perceptions were generally positive but mixed: 47% strongly agreed AI plays an important role in nursing (mean 4.27), and 88% agreed AI would have a place in many nursing applications and practices (mean 4.29). However, 57% agreed AI would threaten/disrupt some nursing careers, and 37% were neutral on whether AI would threaten/disrupt nursing practice.
  • Organizational readiness was unclear: 39% were unsure if someone was in charge of AI at their institute and 34% said no; regarding organizational AI strategy, 40% lacked knowledge of it, 28% said yes, and 32% said no.

Methods

  • Exploratory cross-sectional electronic survey of registered nurses working in UAE government or private hospitals, clinics, or medical centres; convenience sampling was used, with a Google Forms link emailed via nursing department managers. Data collection ran July to November 2021, with reminders every second week.
  • The survey was adapted from previously validated surveys and piloted by three senior nurses and two nurse educators. It captured demographics and nurses’ knowledge, perceptions, organizational readiness, and challenges regarding AI integration.
  • Analysis used SPSS with descriptive statistics (frequencies, percentages, mean, median, standard deviation), Chi-Square tests, and P-values; neutral responses were excluded for some comparisons and agreement/disagreement categories were combined.

Limitations

  • The paper’s stated limitation is brief: it suggests focus group research to facilitate deeper understanding and complement awareness of AI’s role in nursing practice.
  • Evident from the text: the study is cross-sectional, uses convenience sampling, relies on self-reported survey responses, and is limited to nurses in UAE health organizations, so causal inference and broad generalization are constrained.
  • Evident from the text: the methods mention SPSS version 22 and also SPSS version 24, an inconsistency in reporting.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1007/s12553-022-00697-0

Cites

14 of 14 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 11 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    20% of respondents gained AI knowledge through various courses.

    “while 20% of them gained it through various courses.”
    • Also stated in: § Nurses’ knowledge · plain
      “some (n = 113, 20%) gained it through various courses”
    Quote in the paperNot a substantial claim
  • Findingown data

    9% of respondents stated they lack knowledge of AI.

    “while 9% stated they lack knowledge of AI.”
    • Also stated in: § Nurses’ knowledge · plain
      “while others (n = 51, 9%) stated that they lack knowledge of AI”
    Quote in the paperNot a substantial claim
  • Findingown data

    75% of all respondents agreed that the nursing curriculum should include some basic knowledge of AI.

    “75% of all respondents agreed that the nursing curriculum should include some basic knowledge of AI.”
    • Also stated in: § Nurses’ knowledge · plain
      “Most respondents (n = 414, 75%) agreed that the nursing curriculum should include at least some basic knowledge of AI (µ = 3.93, SD = 0.915).”
    Quote in the paperNot a substantial claim
  • Findingown data

    51% of respondents stated their knowledge on AI was obtained through self-taught measures.

    “51% of respondents stated their knowledge on AI was obtained through self-taught measures”
    • Also stated in: § Nurses’ knowledge · plain
      “Most participants obtained knowledge of AI through self-taught measures (n = 283, 51%)”
    Quote in the paperNot a substantial claim
  • Findingown data

    8% of respondents learned AI through postgraduate courses.

    “Only 8% stated they learned through postgraduate courses”
    • Also stated in: § Nurses’ knowledge · plain
      “Only a few (n = 43, 8%) stated they learned through postgraduate courses”
    Quote in the paperNot a substantial claim
  • May combine two claims. 14
  • Classified as probably not a substantial claim. 8

  • May combine two claims.

    Findingown data

    There is an association between the opinion that AI will have a place in many nursing applications and practices and age (p = 0.014), country of education (p = 0.0001), and experience (p = 0.0001).

    “An association was found between the opinion of participants on whether AI will have a place in many nursing applications and practices and the age of participants (p = 0.014), country of education (p = 0.0001), and experience (p = 0.0001).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    203 respondents (36%) agreed they had been trained and educated on AI, 184 (34%) disagreed, and 166 (30%) were neutral.

    “almost equal distribution of responses was received for agreed (n = 203, 36%), disagreed (n = 184, 34%), and neutral (n = 166, 30%) (µ = 3.07, SD = 1.175)”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    There is an association between age and the perception that AI will threaten/disrupt nursing practice (p = 0.037), with participants aged 30-39 and 50-59 inclined to agree.

    “There was an association between the age of participants and their perception of whether AI will threaten/disrupt Nursing practice (p = 0.037), where participants were within age 30–39 years (n = 100, 74%) and those between 50 and 59 years (n = 24, 77%) were inclined to agree to it compared to other age categories.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    70 respondents (13%) were neutral about AI.

    “(n = 70, 13%) were neutral”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    There is an association between respondents' workplace and their perception of AI (p = 0.02), with hospital respondents (98%) tending to agree more than clinic respondents (91%).

    “The study concluded that there is an association between the respondents’ workplace and their perception of AI. The workplace plays an important role (p = 0.02) where the respondents from hospitals (n = 358, 98%) tend to agree more with it compared to the respondents from the clinics (n = 114, 91%).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    There is an association between years of experience and the opinion regarding the threat/disruption AI brings to nursing jobs (p = 0.024), with participants with 6-10 years and 11-20 years more likely to feel threatened.

    “The study revealed an association between the years of experience of the participants and their opinion regarding the threat/disruption AI brings to nursing jobs (p = 0.024), where participants between 6 and 10 years of experience (n = 81, 81%) and those between 11 and 20 years experience (n = 98, 80%) were more likely to feel threatened.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    There is an association between experience and the idea that AI will threaten/disrupt nursing practice (p = 0.006), with participants with 6-10 years and 11-20 years tending to agree.

    “Further, an association was found between the experience of the participants and their idea whether AI will threaten/disrupt the Nursing practice (p = 0.006), where participants in the 6–10 years age group (n = 61, 75%) and those between 11 and 20 years (n = 77, 76%) tend to agree to the idea compared to the others.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    There is an association between perceptions and participants' experience (p = 0.028) and workplace (p = 0.019).

    “There also was an association between the perceptions and participant’s experience (p = 0.028) and workplace (p = 0.019).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    213 respondents (39%) were unsure if someone was in charge of AI at their institutes, while 186 (34%) said no.

    “When asked if someone was in charge of AI at their institutes (n = 213, 39%) said they were unsure. In contrast (n = 186,34%) said no.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The application of AI will continue to increase in healthcare practice and education.

    “There is no doubt that the application of AI will continue to increase in healthcare practice and education [4].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [4] O’Connor S. Artificial intelligence and predictive analytics in nursing education. Nurse Educ Pract [Internet]. 2021;56:103224. Available from: https://doi.org/10.1016/j.nepr.2021.103224. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    553 responses were returned from 650 invitations, giving a response rate of 85%.

    “553 responses were returned from 650 invitation giving a response rate of 85%.”
    • Also stated in: § Demographic information · plain
      “Six hundred and fifty participants were invited, and data was collected from 553 nurses giving a response rate of 85%.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    A recent survey of 675 nurses in the US reported that 30% of respondents know how AI is used in clinical nursing practice, while 70% had fair or no knowledge of the technology employed in AI.

    “A recent survey of 675 nurses in the US reported that 30% of respondents know how AI is used in clinical nursing practice, while 70% had fair or no knowledge of the technology employed in AI [5].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [5] Swan BA, Haas S. a. Assessing the Knowledge and Attitudes of Registered Nurses about Artificial Intelligence in Nursing and Health Care. Nurs Econ. 2021;39(3):139–43.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    The research team adapted a previously validated survey used in similar studies.

    “The research team adapted a previously validated survey used in similar studies [9–11].”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [9] Abuzaid MM, Elshami W, Tekin HIB. Assessment of the Willingness of Radiologists and Radiographers to Accept the Integration of Artificial Intelligence Into Radiology Practice. Acad Radiol. 2022 Oct;29(1):87–94. source

      Not checked in the free run.

    • cites [10] Abuzaid MM, Elshami W, McConnell J, Tekin HO. An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice. Health Technol (Berl) [Internet]. 2021;11(5):1045–50. Available from: https://doi.org/10.1007/s12553-021-00583-1. source

      Not checked in the free run.

    • cites [11] Abuzaid MM, Tekin HO, Reza M, Elhag IR, Elshami W. Assessment of MRI technologists in acceptance and willingness to integrate artificial intelligence into practice. Radiography [Internet]. 2021;27:S83–7. Available from: https://doi.org/10.1016/j.radi.2021.07.007. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    Three senior nurses and two nurse educators piloted the survey to ascertain whether participants understood the questions, as well as the accuracy and dependability of the information.

    “Three senior nurses and two nurse educators piloted the survey to ascertain whether participants understood the questions, as well as the accuracy and dependability of the information.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Most current studies concentrated on AI application development and compared work before and after AI integration; few studies tried to understand the knowledge and readiness to integrate AI in daily practice.

    “However, most current studies concentrated on AI application development and compared the work performed before and after AI integration; few studies tried to understand the knowledge and readiness to integrate AI in their daily practice [6].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [6] Maskara R, Bhootra V, Thakkar D, Nishkalank N. A study on the perception of medical professionals towards artificial intelligence. Int J Multidiscip Res Dev. 2017;4(4):34–9.

      Not checked in the free run.

  • May combine two claims.

    Interpretationcitation

    Our study's knowledge is less than Swan's results as 40% agreed they have AI knowledge while almost similar in basic understanding.

    “Our study’s knowledge is less than Swan’s results as 40% agreed they have AI knowledge while almost similar in the basic understanding (Table 1) [5, 13].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [5] Swan BA, Haas S. a. Assessing the Knowledge and Attitudes of Registered Nurses about Artificial Intelligence in Nursing and Health Care. Nurs Econ. 2021;39(3):139–43.

      Not checked in the free run.

    • cites [13] Taryudi T, Lindayani L, Purnama H, Mutiar A. Nurses’ View towards the Use of Robotic during Pandemic COVID-19 in Indonesia: A Qualitative Study. Open Access Maced J Med Sci. 2022;10:14–8. source

      Not checked in the free run.

    • Rests on an assumption: Participants’ self-reported knowledge of AI accurately reflects their actual knowledge.

  • Classified as probably not a substantial claim.

    Interpretationown data

    AI education is not enough in undergraduate nursing programs and continuous education.

    “First, AI education is not enough in undergraduate nursing programs and continuous education.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Participants’ self-reported knowledge of AI accurately reflects their actual knowledge.

  • May combine two claims.

    Interpretationcitation

    In both studies, more than 70% agreed that AI application would help nurses in work practice with a great understanding of the importance of AI in nurse work.

    “In both studies, more than 70% agreed that AI application would help nurses in work practice with a great understanding of the importance of AI in nurse work [5, 14].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [5] Swan BA, Haas S. a. Assessing the Knowledge and Attitudes of Registered Nurses about Artificial Intelligence in Nursing and Health Care. Nurs Econ. 2021;39(3):139–43.

      Not checked in the free run.

    • cites [14] Booth RG, Strudwick G, McBride S, O’Connor S. Solano López AL. How the nursing profession should adapt for a digital future. BMJ. 2021;373:1–5.

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given

    With increased digitization in healthcare and usage of electronic health data, nursing practice will be greatly impacted.

    “With the increased digitization in healthcare and the usage of electronic health data, nursing practice will be greatly impacted.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given

    The impact of AI in nursing practice will be transformational.

    “Therefore, there is no question that the impact of AI in nursing practice will be transformational.”
    Quote in the paperNot a substantial claim
20 of 20

  • The paper relies on this without support.

    Successful implementation of AI into clinical practice requires a thorough understanding of the attitudes and behaviours of nurses as end-users towards existing and future AI applications.

    “Successful implementation of AI into clinical practice requires a thorough understanding of the attitudes and behaviours of the nurses as end-users towards the existing and future AI applications.”

  • The paper relies on this without support.

    Assessing the current knowledge of AI among nurses is essential to identify future training requirements.

    “Moreover, assessing the current knowledge of AI among nurses is essential to identify future training requirements, as they are the technology users and have direct contact with patients.”

  • The paper relies on this without support.

    The nurses who responded to the survey are representative of nurses in UAE health organisations.

    “Convenience sampling was utilized in this study because it is a simple way to reach out to people in different parts of the UAE.”

  • The paper relies on this without support.

    Participants’ self-reported knowledge of AI accurately reflects their actual knowledge.

    “When asked how well they understood what AI means, 165 respondents (30%) stated that their knowledge is only what they have read in news, posters, or media.”
4 of 4

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?

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.

  • Thirty-three respondents aged 50-59 cannot represent 00%

    Major

    The paper reports 41 respondents aged 50-59. Thirty-three are at least 80.5% of that age group, not 0%; excluding neutral responses would only raise the percentage.

    Reported 0 · recomputed 80.487805

  • Two hundred agreeing Philippine graduates cannot represent 10%

    Major

    Two hundred people are at least 36.2% of the entire 553-person sample, and an even larger percentage of the Philippine-graduate subgroup. The stated 10% is impossible with the reported count.

    Reported 10 · recomputed 36.166365

  • Two SPSS versions are reported for the analysis

    Minor

    The methods state that the data were analyzed using both SPSS version 22 and version 24.

  • The same 144 respondents are described as private-hospital and clinic staff

    Minor

    The results describe 144 respondents as working in private hospitals, but Table 1 labels that same group as working in clinics. These are different workplace categories.

  • Undergraduate-programme agreement is stated as both 75% and 78%

    Minor

    The sentence assigns two different percentages to agreement with including AI in the undergraduate programme.

5 of 5

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. Maskara R, Bhootra V, Thakkar D, Nishkalank N. A study on the perception of medical professionals towards artificial intelligence. Int J Multidiscip Res Dev. 2017;4(4):34–9.

Cited by

Sorted by citations

Related

Authors
Abuzaid, M. M., Elshami, W., & Fadden, S. M.
Affiliations
University of Sharjah (AE)
Corresponding author
Abuzaid, Mohamed M
ORCID
Venue
Health and Technology
Publisher
Springer Science and Business Media LLC
Published
2022-09-14
Volume
12
Issue
6
Pages
1109-1115
ISSN
  • 2190-7188 (ISSN-L)
  • 2190-7196
DOI
10.1007/s12553-022-00697-0
PMC
PMC9470236
OpenAlex
W4295814113
Semantic Scholar
d01b3a34b6df3f990e560457200c24132c0c06d6
Cited by
172
References
14
Citations by year
2026: 48 · 2025: 71 · 2024: 33 · 2023: 18 · 2022: 1
FWCI
9.26
Type
journal article
Language
en
Open access
Licence
Locations
  • Health and Technology (publishedVersion, other-oa)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • Ulster University Research Portal (Ulster University) (publishedVersion, other-oa)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
  • Health Sciences › Nursing › Research and Theory › Nursing education and management
Keywords
artificial intelligence, nursing practice, attitudes toward AI, organizational readiness, AI implementation challenges, nursing curriculum, AI education and training, United Arab Emirates

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