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
Tutkimuksen yleiskatsaus
Tila
Ehdot
Yksityiskohtainen kuvaus
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
Opintotyyppi
Ilmoittautuminen (Arvioitu)
Vaihe
- Ei sovellettavissa
Yhteystiedot ja paikat
Opiskeluyhteys
- Nimi: Seher Gul Yavas, RN
- Puhelinnumero: +90 541 685 8806
- Sähköposti: seher.daglii@gmail.com
Tutki yhteystietojen varmuuskopiointi
- Nimi: Seyda can, Assoc. Prof. Dr.
- Puhelinnumero: +90 536 685 0312
- Sähköposti: seyda.cann@hotmail.com
Opiskelupaikat
-
-
Yalova
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Yalova, Yalova, Turkki (Türkiye)
- Yalova Training and Research Hospital
-
Ottaa yhteyttä:
- Seher Gul Yavas, RN
- Puhelinnumero: +90 541 685 8806
- Sähköposti: seher.daglii@gmail.com
-
-
Osallistumiskriteerit
Kelpoisuusvaatimukset
Opintokelpoiset iät
- Aikuinen
- Vanhempi Aikuinen
Hyväksyy terveitä vapaaehtoisia
Kuvaus
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.
Opintosuunnitelma
Miten tutkimus on suunniteltu?
Suunnittelun yksityiskohdat
- Ensisijainen käyttötarkoitus: Terveyspalvelututkimus
- Jako: Satunnaistettu
- Inventiomalli: Rinnakkaistehtävä
- Naamiointi: Ei mitään (avoin tarra)
Aseet ja interventiot
Osallistujaryhmä / Arm |
Interventio / Hoito |
|---|---|
|
Kokeellinen: 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.
|
|
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.
|
Participants will receive a standard theoretical education session on the nursing process.
|
Mitä tutkimuksessa mitataan?
Ensisijaiset tulostoimenpiteet
Tulosmittaus |
Toimenpiteen kuvaus |
Aikaikkuna |
|---|---|---|
|
Change in Nursing Process Competence
Aikaikkuna: 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)
|
Toissijaiset tulostoimenpiteet
Tulosmittaus |
Toimenpiteen kuvaus |
Aikaikkuna |
|---|---|---|
|
Change in Artificial Intelligence Perception and Attitude
Aikaikkuna: 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).
|
Yhteistyökumppanit ja tutkijat
Sponsori
Opintojen ennätyspäivät
Opi tärkeimmät päivämäärät
Opiskelun aloitus (Arvioitu)
Ensisijainen valmistuminen (Arvioitu)
Opintojen valmistuminen (Arvioitu)
Opintoihin ilmoittautumispäivät
Ensimmäinen lähetetty
Ensimmäinen toimitettu, joka täytti QC-kriteerit
Ensimmäinen Lähetetty (Todellinen)
Tutkimustietojen päivitykset
Viimeisin päivitys julkaistu (Todellinen)
Viimeisin lähetetty päivitys, joka täytti QC-kriteerit
Viimeksi vahvistettu
Lisää tietoa
Tähän tutkimukseen liittyvät termit
Muita asiaankuuluvia MeSH-ehtoja
Muut tutkimustunnusnumerot
- 2026/183
Yksittäisten osallistujien tietojen suunnitelma (IPD)
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