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

NCT07134374 | Completed

• 1 other identifier: Deneme
• Study Type: observational
• Target: 294
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Nurses

Keywords

Artificial Intelligence; Critical Thinking; Nurses; Attitude of Health Personnel; Clinical Decision-Making

Outcome Measures

Primary Outcomes (3)

• 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

Study Arms (1)

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.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Registered nurses

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• TC Erciyes University: lead

Study Sites (1)

Turkish Ministry of Health, Adana City Training and Research Hospital

Sinop, Sinop, 57000, Turkey (Türkiye)

Location

Related Publications (3)

• 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.

  PMID: 32961010 BACKGROUND

• 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.

  PMID: 39794874 BACKGROUND

• 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.

  PMID: 37740191 BACKGROUND

Study Officials

• Abdullah Orhan Demirtaş, Associate Professor

  Adana City Education and Research Hospital

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PhD

Study Record Dates

• First Submitted: August 2, 2025
• First Posted: August 21, 2025
• Study Start: August 20, 2025
• Primary Completion: September 20, 2025
• Study Completion: October 1, 2025
• Last Updated: December 2, 2025

Record last verified: 2025-11

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)