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

24 mei 2026 bijgewerkt door: 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

Studie Overzicht

Toestand

Nog niet aan het werven

Conditie

Interventie / Behandeling

Gedetailleerde beschrijving

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

Studietype

Ingrijpend

Inschrijving (Geschat)

78

Fase

  • Niet toepasbaar

Contacten en locaties

In dit gedeelte vindt u de contactgegevens van degenen die het onderzoek uitvoeren en informatie over waar dit onderzoek wordt uitgevoerd.

Studiecontact

Studie Contact Back-up

Studie Locaties

Deelname Criteria

Onderzoekers zoeken naar mensen die aan een bepaalde beschrijving voldoen, de zogenaamde geschiktheidscriteria. Enkele voorbeelden van deze criteria zijn iemands algemene gezondheidstoestand of eerdere behandelingen.

Geschiktheidscriteria

Leeftijden die in aanmerking komen voor studie

  • Volwassen
  • Oudere volwassene

Accepteert gezonde vrijwilligers

Ja

Beschrijving

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.

Studie plan

Dit gedeelte bevat details van het studieplan, inclusief hoe de studie is opgezet en wat de studie meet.

Hoe is de studie opgezet?

Ontwerpdetails

  • Primair doel: Onderzoek naar gezondheidsdiensten
  • Toewijzing: Gerandomiseerd
  • Interventioneel model: Parallelle opdracht
  • Masker: Geen (open label)

Wapens en interventies

Deelnemersgroep / Arm
Interventie / Behandeling
Experimenteel: 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.
Gedragsmatig: 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.
Gedragsmatig: Standard Theoretical Education on the Nursing Process
Participants will receive a standard theoretical education session on the nursing process.
Actieve vergelijker: 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.
Gedragsmatig: Standard Theoretical Education on the Nursing Process
Participants will receive a standard theoretical education session on the nursing process.

Wat meet het onderzoek?

Primaire uitkomstmaten

Uitkomstmaat
Maatregel Beschrijving
Tijdsspanne
Change in Nursing Process Competence
Tijdsspanne: 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)

Secundaire uitkomstmaten

Uitkomstmaat
Maatregel Beschrijving
Tijdsspanne
Change in Artificial Intelligence Perception and Attitude
Tijdsspanne: 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).

Medewerkers en onderzoekers

Hier vindt u mensen en organisaties die betrokken zijn bij dit onderzoek.

Sponsor

University of Yalova

Studie record data

Deze datums volgen de voortgang van het onderzoeksdossier en de samenvatting van de ingediende resultaten bij ClinicalTrials.gov. Studieverslagen en gerapporteerde resultaten worden beoordeeld door de National Library of Medicine (NLM) om er zeker van te zijn dat ze voldoen aan specifieke kwaliteitscontrolenormen voordat ze op de openbare website worden geplaatst.

Bestudeer belangrijke data

Studie start (Geschat)

1 juni 2026

Primaire voltooiing (Geschat)

31 december 2026

Studie voltooiing (Geschat)

31 december 2026

Studieregistratiedata

Eerst ingediend

24 mei 2026

Eerst ingediend dat voldeed aan de QC-criteria

24 mei 2026

Eerst geplaatst (Werkelijk)

1 juni 2026

Updates van studierecords

Laatste update geplaatst (Werkelijk)

1 juni 2026

Laatste update ingediend die voldeed aan QC-criteria

24 mei 2026

Laatst geverifieerd

1 mei 2026

Meer informatie

Termen gerelateerd aan deze studie

Trefwoorden

Aanvullende relevante MeSH-voorwaarden

Andere studie-ID-nummers

  • 2026/183

Plan Individuele Deelnemersgegevens (IPD)

Bent u van plan om gegevens van individuele deelnemers (IPD) te delen?

NEE

Informatie over medicijnen en apparaten, studiedocumenten

Bestudeert een door de Amerikaanse FDA gereguleerd geneesmiddel

Nee

Bestudeert een door de Amerikaanse FDA gereguleerd apparaatproduct

Nee

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