The goal of this randomized controlled study is to determine the impact of ChatGPT based nursing process training on nursing students' clinical decision-making competencies and artificial intelligence anxiety. Population and Sample: The population of the research consists of senior students studying at Gülhane Faculty of Nursing, University of Health Sciences. Power analysis was performed to determine the number of people to be included in the study. The power of the test was calculated with the G\*Power 3.1 program. In a similar study in the relevant literature, the effect size regarding the change in clinical decision-making level was calculated as 0.898. In order to exceed the 99% value in determining the power of the study; At the 5% significance level and 0.898 effect size, 44 people, 22 people in the groups, need to be reached (df=21; t=1.721). In the research, it was aimed to reach a total of 60 people, 30 people in the groups, considering the high power of the test and the losses.
Nurses, who are important members of the healthcare team, often encounter situations in the clinic that require them to make decisions. Nurses need to make a complex evaluation by using critical thinking and problem-solving skills in clinical decision-making.During nursing education, it is aimed at helping students acquire the skills to make this complex evaluation. To gain these skills, real-life experiences during clinical practices, case discussions, simulations, and skill laboratories can be used. It is thought that artificial intelligence applications, which have been increasingly used in recent years, can contribute to the development of clinical decision-making skills in nursing education. In this regard, this study aimed to investigate the effect of ChatGPT use training in the nursing process on nursing students' clinical decision-making competencies and artificial intelligence anxiety.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
SINGLE
Enrollment
60
ChatGPT Based Nursing Process Training topics: Lesson 1: Use of artificial intelligence and ChatGPT in healthcare Lesson 2: Using ChatGPT in determining nursing diagnoses and goals Lesson 3: Using ChatGPT to determine nursing interventions Lesson 4: Things to consider and ethical principles when using ChatGPT when creating a nursing process.
Miray AKSU
Ankara, Çankaya, Turkey (Türkiye)
Descriptive Information Form
It was prepared by the researchers and consists of 6 questions regarding demographic characteristics and the use of artificial intelligence.
Time frame: 6 weeks
Clinical Decision Making Scale in Nursing
The scale, which was developed to measure the clinical decision-making perceptions of nursing students based on their self-expression, was adapted into Turkish. The scale, which consists of four sub-dimensions, has 40 items. Sub-dimensions; It is stated as searching for options, declaring goals and values, evaluating and re-evaluating the results, searching for information and impartial assimilation of new information. Each subscale consists of 10 items. In the scale, 18 negative items are scored reversely. The five-point Likert type scale is scored as "Always-5, Frequently-4, Sometimes-3, Rarely-2 and Never-1" and the lowest and highest values are 40-200 for the total score of the scale and 40-200 for each sub-dimension. It varies between 10-50. High scores from the scale indicate that the perception of decision-making is high, while low scores indicate that the perception of decision-making is low.
Time frame: 6 weeks
Artificial Intelligence Anxiety Scale:
Artificial Intelligence Anxiety Scale developed by Wang and Wang (2019) was adapted into Turkish by Akkaya et al (2021). The Turkish form of YZKS consists of 16 items and 4 dimensions and is a 5-point Likert type scale. The sub-dimensions are learning, job switching, sociotechnical blindness and artificial intelligence configuration.
Time frame: 6 weeks
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