White Anne, Maguire Mary Beth, Brown Austin
Wellstar School of Nursing, Kennesaw State University, Kennesaw, GA 30144, USA.
School of Data Science and Analytics, Kennesaw State University, Kennesaw, GA 30144, USA.
Nurs Rep. 2024 Dec 3;14(4):3819-3829. doi: 10.3390/nursrep14040279.
BACKGROUND/OBJECTIVES: The projected increase from 58 million older adults in 2022 to 82 million by 2050 in the United States highlights the urgency of preparing nursing students to care for this aging population. However, studies reveal negative attitudes among nursing students toward older adults. A three-phased educational intervention that included an artificial intelligence (AI)-driven virtual simulation was implemented to address this. AI-generated simulations promise to expose marginalized groups and strengthen future nurses' knowledge, skills, and attitudes.
A convergent mixed-method design was used to measure the change in nursing students' attitudes toward older adults, as measured by the UCLA Geriatrics Attitudes Survey and a Guided Reflection survey after participating in an Artificial Intelligence in Education learning event ( = 151).
The results indicate that post-intervention scores (M = 35.07, SD = 5.34) increased from pre-intervention scores (M = 34.50, SD = 4.86). This difference was statistically significant at the 0.10 significance level (t = 1.88, = 0.06). The qualitative analysis indicated that the attitudes impacted were challenging and overcoming ageism, increased empathy and patience, and enhanced communication skills.
Utilizing artificial intelligence technology during educational events effectively yields measurable learning outcomes. Cultivating positive attitudes toward older adults is essential for competent care in an aging society. This study was prospectively approved by the university's Institutional Review Board (IRB) on 30 July 2021, IRB-FY22-3.
背景/目标：预计美国65岁及以上的老年人数量将从2022年的5800万增加到2050年的8200万，这凸显了培养护理专业学生照顾这一老龄人口的紧迫性。然而，研究显示护理专业学生对老年人持消极态度。为此实施了一项分三个阶段的教育干预措施，其中包括人工智能驱动的虚拟模拟。人工智能生成的模拟有望让边缘化群体得到关注，并增强未来护士的知识、技能和态度。
采用聚合混合方法设计，通过加州大学洛杉矶分校老年医学态度调查和参与教育中的人工智能学习活动后的引导反思调查（n = 151），来衡量护理专业学生对老年人态度的变化。
结果表明，干预后得分（M = 35.07，标准差 = 5.34）高于干预前得分（M = 34.50，标准差 = 4.86）。在0.10的显著性水平上，这种差异具有统计学意义（t = 1.88，p = 0.06）。定性分析表明，受到影响的态度包括挑战和克服年龄歧视、增强同理心和耐心以及提高沟通技巧。
在教育活动中使用人工智能技术能有效产生可衡量的学习成果。在老龄化社会中，培养对老年人的积极态度对于提供称职的护理至关重要。本研究于2021年7月30日获得大学机构审查委员会（IRB）的前瞻性批准，IRB-FY22-3。
