Impact of Innovative ECG Training Using AI-Supported Clinical Scenarios on Knowledge, Clinical Reasoning, and Self-Efficacy Among Nursing Staff
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 64
- 试验地点
- 1
- 主要终点
- Electrocardiogram Interpretation Knowledge Score
研究概览
简要总结
Background and Purpose Accurate interpretation of an Electrocardiogram is a vital skill for nursing staff to ensure patient safety and timely intervention in cardiovascular care. Traditional training methods often lack the interactive and complex nature of real-life clinical situations. This study aims to evaluate the effectiveness of an innovative training program that uses Artificial Intelligence to create realistic clinical scenarios. The goal is to determine if this technology-enhanced approach improves nurses' knowledge, their ability to make clinical decisions (clinical reasoning), and their confidence in performing these tasks (self-efficacy).
Study Design and Methodology The researchers will conduct a study involving nursing staff to compare their performance before and after the training intervention. Participants will engage with Artificial Intelligence supported clinical scenarios specifically designed for Electrocardiogram interpretation.
Data Collection
To measure the impact of the training, the study will use four primary tools:
An Electrocardiogram Interpretation Knowledge Test to measure theoretical understanding.
An assessment of Nursing Decision-Making in Electrocardiogram Interpretation to evaluate practical clinical reasoning.
A Self-Efficacy Scale for Artificial Intelligence-based Electrocardiogram Training to measure the participants' confidence in their skills.
Focus group discussions will be held at the end of the study to gain deeper qualitative insights into the nursing staff's experiences and perceptions of using technology in their professional development.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Health Services Research
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Nursing staff currently employed in clinical practice.
- •Willingness to participate in the study and provide written informed consent.
- •Ability to use basic computer software or mobile applications to interact with the Artificial Intelligence platform.
排除标准
- •Nurses who have attended advanced Electrocardiogram certification courses or specialized training within the past three months to avoid bias in the baseline knowledge assessment.
- •Nurses who have previously participated in formal training or research studies involving Artificial Intelligence-driven educational platforms or clinical decision-support systems to ensure responses and perceived self-efficacy are not influenced by prior familiarity.
研究组 & 干预措施
Artificial Intelligence Driven Training Group
Participants in this group will utilize an original, specifically designed learning software developed by the researcher that integrates Artificial Intelligence to provide dynamic clinical scenarios. The intervention focuses on interactive training for Electrocardiogram interpretation. Each scenario is tailored to the learner's performance, providing immediate feedback and simulating real-world cardiovascular care challenges. This group will complete pre-test and post-test assessments, followed by focus group discussions to explore their qualitative experiences with the software.
干预措施: Artificial Intelligence Driven Scenario-Based Learning Software (Device)
Traditional Training Control Group
Participants in this group will receive the standard educational intervention for Electrocardiogram interpretation used in traditional nursing education. This typically includes conventional classroom lectures, printed educational materials, and standard presentation slides without the interactive or adaptive features of Artificial Intelligence. This group will complete the same pre-test and post-test assessments as the intervention group to provide a baseline for comparing the effectiveness of the new technology-enhanced method.
干预措施: Traditional Electrocardiogram Educational Program (Other)
结局指标
主要结局
Electrocardiogram Interpretation Knowledge Score
时间窗: Baseline (Pre-test) and 2 weeks post-intervention (Post-test)
A comprehensive assessment tool designed to evaluate the theoretical and practical knowledge of nursing staff: Consists of 15 multiple-choice questions specifically designed to assess the cognitive knowledge level of nurses regarding the fundamental principles of Electrocardiogram interpretation.such as analysis of basic waveform components, calculating heart rate, identification of common arrhythmias, atrioventricular conduction abnormalities, and evaluation of life-threatening cardiac rhythms. Each correct answer is awarded one point, with a total possible score of 15. where scores range from a minimum of 0 to a maximum of 15, Higher scores indicate a higher level of knowledge in Electrocardiogram interpretation.
次要结局
- Nursing Decision-Making Scale in Electrocardiogram Interpretation(Baseline (Pre-test) and 2 weeks post-intervention (Post-test))
- General Self-Efficacy Scale for Electrocardiogram Interpretation and Clinical Tasks(Baseline (Pre-test) and two weeks after the completion of the training intervention (Follow-up test).)
- Nurses' Perception and Satisfaction with Artificial Intelligence-Assisted Learning in Electrocardiogram Interpretation(Baseline (Pre-test) and 2 weeks post-intervention (Post-test))
- Nursing Clinical Decision-Making Score using Case Vignettes(Baseline (Pre-test) and 2 weeks post-intervention (Post-test))
研究者
Mohamed Fakhry Ahmed Salem
Lecturer of Medical-Surgical Nursing
Alexandria University