Nurses' Attitudes Toward Artificial Intelligence and Their Relationship With Critical Thinking Dispositions (AI)

Investigation of the Relationship Between Nurses' Attitudes Toward Artificial Intelligence and Their Critical Thinking Dispositions

The integration of artificial intelligence (AI) into healthcare is gaining momentum, particularly in areas such as diagnosis, treatment planning, and patient monitoring. While AI offers the promise of increased efficiency and support for evidence-based care, its success depends not only on technology but also on the attitudes and cognitive skills of healthcare professionals. Nurses, who are at the center of patient care, are expected to interact with AI systems. This may require nurses to adapt to new roles and develop critical thinking skills to interpret AI outputs correctly. Despite the growing importance of these factors, no study has examined the relationship between nurses' attitudes toward AI and their critical thinking tendencies. This study, conducted among nurses at Adana City Training and Research Hospital, aims to examine this relationship and contribute to educational and professional development strategies that support the safe and effective use of AI in nursing practice.

Study Overview

• Status: Completed
• Conditions: Nurses

Detailed Description

Today's healthcare system is rapidly evolving with technological transformations, and artificial intelligence (AI) technologies are at the center of this transformation. AI-supported applications in many areas, from diagnosis to treatment planning, patient monitoring systems to medication management, have the potential to optimize clinical decision-making processes and increase efficiency in healthcare services. However, the effective integration of these technologies and their adoption by healthcare professionals depends not only on technical infrastructure but also on users' attitudes and cognitive competencies.

Nurses, an integral part of healthcare services, are a key professional group that will interact directly with AI technologies in patient care processes. The integration of artificial intelligence into nursing practices is manifested in various forms, such as smart patient monitoring systems, virtual nursing assistants, clinical decision support systems, and even robotic assistants. While these innovations hold the promise of reducing nurses' workloads, minimizing errors, and helping them make more evidence-based decisions, they also present a number of challenges, including the transformation of professional roles and new competency requirements. Nurses' attitudes toward artificial intelligence have emerged as a critical determinant factor in the successful adoption and integration of these technologies into hospital environments and daily practice. The literature suggests that healthcare workers' negative attitudes toward new technologies can slow down or even hinder adaptation processes. Conversely, positive attitudes can make nurses more open to learning, increase their willingness to adopt technology, and boost their motivation to integrate it into clinical practice.

On the other hand, critical thinking skills, one of the cornerstones of the nursing profession, refer to the ability to make correct decisions in complex clinical scenarios, implement evidence-based practices, and resolve ethical dilemmas. Although AI systems analyze large datasets to make recommendations, the human factor remains crucial in evaluating the accuracy, reliability, and patient-specific appropriateness of these recommendations. A diagnosis suggestion or treatment plan provided by an AI system should not be blindly accepted by the nurse but critically evaluated, taking into account the source and validity of the information as well as the patient's individual characteristics. For example, an AI algorithm may recommend a medication based on certain symptoms, but the nurse's critical assessment of the patient's allergy history, other drug interactions, or socioeconomic status ensures safe and effective care. In this context, critical thinking serves as a bridge to ensure that AI-supported decisions are consistent with the patient's unique needs and overall care philosophy.

A review of the existing literature indicates that there are studies that examine healthcare professionals' attitudes toward AI or their critical thinking tendencies separately. However, no studies have directly examined the potential relationship between nurses' attitudes toward AI and their critical thinking tendencies. This relationship could provide important insights into how AI should be integrated into nursing education and professional development. If nurses who exhibit positive attitudes toward AI also demonstrate higher critical thinking tendencies, this would highlight the importance of designing AI education programs that encourage critical thinking. Alternatively, if the opposite is true, different strategies may need to be developed to address how negative attitudes may influence critical thinking processes.

Nurses working in large and busy healthcare institutions such as Adana City Training and Research Hospital serve a wide patient population and encounter various technological tools. Understanding the attitudes of nurses working at this hospital toward AI and their critical thinking tendencies will contribute to the hospital's own technology integration strategies and serve as a model for similar-scale healthcare institutions in Turkey. This research will provide an evidence-based foundation for developing educational programs and curriculum updates that facilitate the adoption and safe use of AI in nursing practice. Ultimately, such information will directly contribute to improving patient care quality and strengthening professional adaptation by guiding the development of the necessary competencies for nurses to work effectively and harmoniously with AI in future healthcare systems.

• Study Type: Observational
• Enrollment (Actual): 294

Contacts and Locations

Study Locations

• Turkey (Türkiye)
  • Sinop
    • Sinop, Sinop, Turkey (Türkiye), 57000
      • Turkish Ministry of Health, Adana City Training and Research Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Registered nurses

Description

Inclusion Criteria:

• Nurses who are actively working in a university hospital,
• Have at least 6 months of professional experience, and
• Are willing to participate in the research.

Exclusion Criteria:

• Refusal to Participate: Nurses who declined to participate in the study or who did not wish to sign the informed consent form.
• On Leave: Nurses who are on leave, annual leave, maternity leave, or parental leave during the conduct of the study.
• Communication Barriers: Nurses with language barriers that significantly impair their ability to read and understand the questionnaire or who are known to have severe cognitive impairments.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Registered Nurses; This cross-sectional study includes participants who are registered nurses working actively in a university hospital and who volunteered to participate in the study. The group includes nurses aged 18 and older who possess sufficient language and cognitive skills to complete the study. All participants have clinical experience. The study aims to investigate the potential relationship between attitudes toward artificial intelligence and critical thinking tendencies. No intervention is applied, and data are collected through self-report questionnaires validated for validity at a single time point.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Attitude Toward Artificial Intelligence	This criterion is an assessment designed to determine nurses' general attitudes toward artificial intelligence technologies in healthcare services. Participants are given a validated "Attitude Toward AI Scale" and numerical scores are obtained. The minimum score on the scale is 20; the maximum score is 100. As attitude scores increase, attitudes toward artificial intelligence are interpreted as more positive.	Baseline
Critical Thinking Disposition	This criterion aims to determine nurses' propensity for critical thinking. Participants are assessed using the "Marmara Critical Thinking Propensity Scale." The minimum score on the scale is 28; the maximum score is 140. A higher score indicates a higher critical thinking tendency.The scores obtained indicate the extent to which individuals are prone to critical thinking skills; high scores indicate a stronger propensity for critical thinking.	Baseline
The Relationship Between Attitude Toward Artificial Intelligence and Critical Thinking Disposition	This criterion aims to analyze whether there is a statistically significant relationship between nurses' attitudes toward artificial intelligence and their critical thinking tendencies. Using correlation, regression, or appropriate statistical analyses, the study evaluates whether there is a positive, negative, or insignificant relationship between the two variables. These findings may provide guidance for shaping artificial intelligence education and clinical practices.	Baseline

Collaborators and Investigators

• Sponsor: TC Erciyes University
• Investigators: Study Director: Abdullah Orhan Demirtaş, Associate Professor, Adana City Education and Research Hospital

Publications and helpful links

General Publications

• Johnson KB, Wei WQ, Weeraratne D, Frisse ME, Misulis K, Rhee K, Zhao J, Snowdon JL. Precision Medicine, AI, and the Future of Personalized Health Care. Clin Transl Sci. 2021 Jan;14(1):86-93. doi: 10.1111/cts.12884. Epub 2020 Oct 12.
• Nashwan AJ, Cabrega JA, Othman MI, Khedr MA, Osman YM, El-Ashry AM, Naif R, Mousa AA. The evolving role of nursing informatics in the era of artificial intelligence. Int Nurs Rev. 2025 Mar;72(1):e13084. doi: 10.1111/inr.13084.
• Alowais SA, Alghamdi SS, Alsuhebany N, Alqahtani T, Alshaya AI, Almohareb SN, Aldairem A, Alrashed M, Bin Saleh K, Badreldin HA, Al Yami MS, Al Harbi S, Albekairy AM. Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Med Educ. 2023 Sep 22;23(1):689. doi: 10.1186/s12909-023-04698-z.

Study record dates

Study Major Dates

• Study Start (Actual): August 20, 2025
• Primary Completion (Actual): September 20, 2025
• Study Completion (Actual): October 1, 2025

Study Registration Dates

• First Submitted: August 2, 2025
• First Submitted That Met QC Criteria: August 13, 2025
• First Posted (Actual): August 21, 2025

Study Record Updates

• Last Update Posted (Actual): December 2, 2025
• Last Update Submitted That Met QC Criteria: November 29, 2025
• Last Verified: November 1, 2025

More Information

Terms related to this study

• Keywords: Artificial Intelligence; Clinical Decision-Making; Nurses; Attitude of Health Personnel; Critical Thinking
• Other Study ID Numbers: Deneme

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Not applicable. No individual participant data (IPD) will be shared.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No