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
調査の概要
状態
条件
詳細な説明
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
,
. 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)
,
. 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
,
. 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
研究の種類
入学 (推定)
段階
- 適用できない
連絡先と場所
研究連絡先
- 名前：Seher Gul Yavas, RN
- 電話番号：+90 541 685 8806
- メール：seher.daglii@gmail.com
研究連絡先のバックアップ
- 名前：Seyda can, Assoc. Prof. Dr.
- 電話番号：+90 536 685 0312
- メール：seyda.cann@hotmail.com
研究場所
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Yalova
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Yalova、Yalova、トルコ（Türkiye）
- Yalova Training and Research Hospital
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コンタクト：
- Seher Gul Yavas, RN
- 電話番号：+90 541 685 8806
- メール：seher.daglii@gmail.com
-
-
参加基準
適格基準
就学可能な年齢
- 大人
- 高齢者
健康ボランティアの受け入れ
説明
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.
研究計画
研究はどのように設計されていますか？
デザインの詳細
- 主な目的：ヘルスサービス研究
- 割り当て：ランダム化
- 介入モデル：並列代入
- マスキング：なし（オープンラベル）
武器と介入
参加者グループ / アーム |
介入・治療 |
|---|---|
|
実験的：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.
|
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.
|
|
アクティブコンパレータ：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.
|
Participants will receive a standard theoretical education session on the nursing process.
|
この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Change in Nursing Process Competence
時間枠：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)
|
二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Change in Artificial Intelligence Perception and Attitude
時間枠：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).
|
協力者と研究者
スポンサー
研究記録日
主要日程の研究
研究開始 (推定)
一次修了 (推定)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
この情報は、Web サイト clinicaltrials.gov から変更なしで直接取得したものです。研究の詳細を変更、削除、または更新するリクエストがある場合は、register@clinicaltrials.gov。 までご連絡ください。 clinicaltrials.gov に変更が加えられるとすぐに、ウェブサイトでも自動的に更新されます。