The Effect of AI-Assisted Nursing Process Training on Nursing Process Competence, Perception and Attitudes Towards Artificial Intelligence in Nurses: A Randomized Controlled Study

May 24, 2026 updated by: Seher Dağlı, University of Yalova

Hemşirelerde Yapay Zeka Destekli Hemşirelik Süreci Eğitiminin Hemşirelik Süreci Yetkinliğine, Yapay Zeka Algı ve Tutumuna Etkisi: Randomize Kontrollü Bir Çalışma

This study aims to determine how applied artificial intelligence (AI) training affects nurses' ability to manage the nursing process and their perceptions and attitudes toward AI technology

  • The nursing process is a scientific, six-stage approach used by nurses to identify patient needs and provide holistic care

The research is a randomized controlled trial involving 78 nurses at Yalova Education and Research Hospital

. Participants will be split into two groups: Both groups will receive standard theoretical training on the nursing process

. The intervention group will receive additional specialized training on using AI tools (such as ChatGPT and Deepseek) to help create nursing care plans through practical case studies

. Nurses' skills and views will be measured using specific scales before the training and one month after the intervention to evaluate the training's effectiveness

  • This study is expected to provide valuable insights into how AI can support clinical decision-making and help healthcare providers adapt to new technologies
  • The research has been approved by the Yalova University Ethics Committee (Protocol 2026/183) and will be conducted between May and December 2026

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Detailed Description

This randomized controlled, quasi-experimental study is designed to evaluate the impact of an applied artificial intelligence (AI)-supported nursing process training program on nurses' professional competence and their attitudes toward AI technology. The primary objective is to determine how the integration of AI tools into clinical decision-making affects nursing process efficiency and perception among healthcare professionals

. Methodology and Randomization: The study population consists of 414 nurses working at Yalova Education and Research Hospital

  • Based on power analysis (power=0.95, alpha=0.05), a total of 78 nurses will be recruited and randomized into two groups: an intervention group (n=39) and a control group (n=39)
  • Randomization will be conducted following the collection of baseline (pre-test) data

Intervention Protocol:

Phase 1 (Common Foundation): Both the intervention and control groups will receive a "Theoretical Training on the Nursing Process" to ensure baseline knowledge standardization . Phase 2 (AI Training - Intervention Group only): The intervention group will receive "AI-Supported Nursing Process Theoretical Training," which includes technical guidance on using AI tools (such as ChatGPT and Deepseek) for clinical care

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. Phase 3 (Practical Application - Intervention Group only): Participants will engage in hands-on workshops using structured clinical cases. They will apply AI tools to generate care plans based on NANDA-I, NIC, and NOC taxonomies

  • This phase includes structured debriefing and feedback sessions led by the researcher

The control group will only receive the standard theoretical nursing process education and will not have access to the AI training modules until the study is completed .

Data Collection and Assessment: Data will be collected using three instruments:

The Nurse Information Form (demographics and AI usage habits) . The Nursing Process Competence Scale (to measure clinical workflow skills)

. The Artificial Intelligence Perception and Attitude Scale (YAZAT-24) (to measure attitudes toward AI integration)

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. Measurements will be conducted at two time points: baseline (pre-test) and one month following the intervention (post-test) to assess long-term retention and impact

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. Statistical Analysis: Data analysis will be performed using SPSS 22.0. Normality will be assessed via the Kolmogorov-Smirnov test. Analysis will include descriptive statistics, independent samples t-test or Mann-Whitney U for group comparisons, and Repeated Measures ANOVA or Friedman tests for within-group changes over time

Study Type

Interventional

Enrollment (Estimated)

78

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Volunteering to participate in the study.
  • Working actively as a nurse in the specified institution (Yalova Training and Research Hospital).
  • Not having previously used artificial intelligence in the nursing process.

Exclusion Criteria:

  • Refusing to participate in the study.
  • Having previously used artificial intelligence in the nursing process. Submitting incomplete data collection forms.
  • Requesting to withdraw from the study.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Intervention Group
Participants will receive a standard theoretical education session on the nursing process. Following this, they will receive an applied artificial intelligence-supported nursing process training and engage in case study practices using AI tools.
Behavioral: Artificial Intelligence-Supported Nursing Process Training
Participants will receive theoretical education on the artificial intelligence-supported nursing process and engage in applied case studies using AI tools in small groups.
Behavioral: Standard Theoretical Education on the Nursing Process
Participants will receive a standard theoretical education session on the nursing process.
Active Comparator: Control Group
Participants will receive only the standard theoretical education session on the nursing process. They will not receive the artificial intelligence-supported training or case study practices during the study period.
Behavioral: Standard Theoretical Education on the Nursing Process
Participants will receive a standard theoretical education session on the nursing process.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Change in Nursing Process Competence
Time Frame: Baseline (pre-test) and 1 month after the intervention (post-test)
This outcome is measured using the Nursing Process Competence Scale. The scale consists of 24 items and 5 sub-dimensions evaluated on a 5-point Likert scale. The average score ranges from 1 to 5, and higher scores indicate higher nursing process competence
Baseline (pre-test) and 1 month after the intervention (post-test)

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Change in Artificial Intelligence Perception and Attitude
Time Frame: Baseline (pre-test) and 1 month after the intervention (post-test).
This outcome is measured using the Artificial Intelligence Perception and Attitude Scale (YAZAT-24). The scale consists of 24 items and 4 sub-dimensions evaluated on a 7-point Likert scale. Higher total scores indicate more positive perceptions and attitudes towards artificial intelligence.
Baseline (pre-test) and 1 month after the intervention (post-test).

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University of Yalova

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

June 1, 2026

Primary Completion (Estimated)

December 31, 2026

Study Completion (Estimated)

December 31, 2026

Study Registration Dates

First Submitted

May 24, 2026

First Submitted That Met QC Criteria

May 24, 2026

First Posted (Actual)

June 1, 2026

Study Record Updates

Last Update Posted (Actual)

June 1, 2026

Last Update Submitted That Met QC Criteria

May 24, 2026

Last Verified

May 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2026/183

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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