挖掘意识:通过使用机器学习方法进行横断研究来评估护理学生的水消费行为和可持续性感知
Aycan Kucukkuya1, Gonul Bodur2, Sabri Yasir Ozata3
1Hematology Department, Koc University Hospital, Istanbul, Turkey.
Public health nursing (Boston, Mass.)
|October 28, 2024
概括
护理学生表现出对水资源短缺的认识,但个人水足迹知识有限. 家庭用水效率显著影响他们对水资源可持续性的看法.
科学领域:
- 环境科学 环境科学
- 公共卫生 公共卫生
- 机器学习应用 机器学习应用
背景情况:
- 有效的水资源管理需要了解护理学生的水消耗行为和可持续性感知.
- 护理学生的参与对于促进医疗保健机构内的可持续实践至关重要.
- 这项研究解决了未来医疗保健专业人员对水可持续性意识的知识差距.
研究的目的:
- 调查护理学生的水消费行为和对水可持续性的看法.
- 用先进的机器学习 (ML) 技术分析学生行为和感知的复杂模式和相关性.
- 确定影响这一人口群体对水资源可持续性的态度的关键因素.
主要方法:
- 在土耳其伊斯坦布尔,对182名高级护理学生进行了一项描述性的横截面研究.
- 数据通过在线调查收集,其中包括一个信息表格,一个用于水稀缺预测 (VAS) 的视觉模拟尺度和一个水消耗行为尺度.
- 使用先进的机器学习技术,分析与水资源可持续性相关的行为模式和观念.
主要成果:
- 护理学生主要使用包装水,并认为存在严重的水资源短缺威胁,但对个人水足迹的认识有限.
- 高VAS分数表明全球水危机意识强,但对当地水资源短缺持怀疑态度.
- 机器学习确定"家庭用水效率"是影响水可持续性态度的主要因素,其次是"水意识"和"可持续水道".
结论:
- 显然需要将可持续水资源管理教育纳入护理课程.
- 这些发现表明,护理学生具有基本的意识和准备,以采用可持续的水务实践.
- 教育干预措施可以提高个人水足迹意识,并促进护理学生之间更可持续的行为.
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