The Effect of AI-Assisted Nursing Process Training on Nursing Process Competence, Perception and Attitudes Towards Artificial Intelligence in Nurses: A Randomized Controlled Study
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
연구 개요
상태
정황
상세 설명
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
연구 유형
등록 (추정된)
단계
- 해당 없음
연락처 및 위치
연구 연락처
- 이름: Seher Gul Yavas, RN
- 전화번호: +90 541 685 8806
- 이메일: seher.daglii@gmail.com
연구 연락처 백업
- 이름: Seyda can, Assoc. Prof. Dr.
- 전화번호: +90 536 685 0312
- 이메일: seyda.cann@hotmail.com
연구 장소
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Yalova
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Yalova, Yalova, 터키 (Türkiye)
- Yalova Training and Research Hospital
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연락하다:
- Seher Gul Yavas, RN
- 전화번호: +90 541 685 8806
- 이메일: seher.daglii@gmail.com
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참여기준
자격 기준
공부할 수 있는 나이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
설명
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.
공부 계획
연구는 어떻게 설계됩니까?
디자인 세부사항
- 주 목적: 건강 서비스 연구
- 할당: 무작위
- 중재 모델: 병렬 할당
- 마스킹: 없음(오픈 라벨)
무기와 개입
참가자 그룹 / 팔 |
개입 / 치료 |
|---|---|
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실험적: 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.
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Participants will receive theoretical education on the artificial intelligence-supported nursing process and engage in applied case studies using AI tools in small groups.
Participants will receive a standard theoretical education session on the nursing process.
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활성 비교기: 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.
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Participants will receive a standard theoretical education session on the nursing process.
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연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Change in Nursing Process Competence
기간: Baseline (pre-test) and 1 month after the intervention (post-test)
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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
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Baseline (pre-test) and 1 month after the intervention (post-test)
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2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Change in Artificial Intelligence Perception and Attitude
기간: Baseline (pre-test) and 1 month after the intervention (post-test).
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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.
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Baseline (pre-test) and 1 month after the intervention (post-test).
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공동 작업자 및 조사자
연구 기록 날짜
연구 주요 날짜
연구 시작 (추정된)
기본 완료 (추정된)
연구 완료 (추정된)
연구 등록 날짜
최초 제출
QC 기준을 충족하는 최초 제출
처음 게시됨 (실제)
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
QC 기준을 충족하는 마지막 업데이트 제출
마지막으로 확인됨
추가 정보
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