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作为身体训练有素的老年人孤独的重要调节风险因素的有氧健身:使用机器学习的解释性案例研究

Samuel Encarnação^1,2,3, Paula Vaz², Álvaro Fortunato^1,4

¹Department of Sport Sciences, Instituto Politécnico de Bragança (IPB), 5300-253 Bragança, Portugal.

Life (Basel, Switzerland)

|June 28, 2023

概括

身体健康,包括有氧健身和力量,显著影响老年人的孤独感. 更高的健身水平,特别是有氧能力,与减少孤独感有关.

科学领域:

老年学是一门学科.
计算社会科学计算社会科学
运动科学运动科学

背景情况:

孤独感在老年人群中是一个越来越大的问题.
了解导致老年人孤独的因素对于公共健康至关重要.

研究的目的:

采用机器学习算法来分析训练有素的老年人中社会人口统计因素,身体健康,体力活动水平和久坐行为与孤独之间的关系.
确定这一人口群体中孤独的关键预测因素.

主要方法:

利用UCLA孤独度量和功能适应性测试电池进行数据收集.
应用了纯粹的贝叶斯机器学习算法,并对23名经过体力训练的老年人进行了交叉验证 (LOOCV).
评估社会人口统计学变量,身体健康 (有氧健身,手握强度,上肢强度),身体活动水平和久坐行为.

主要成果:

朴素的贝叶斯模型在识别导致高度孤独的因素方面实现了100%的准确性和F-1分数.
有氧健身 (AF),手握强度 (HG) 和上肢强度 (ULS) 被确定为与孤独感增加相关的最相关变量.
该模型在预测孤独时表现出高精度.

结论:

机器学习,特别是使用LOOCV的天真贝叶斯算法,可以有效地预测受过训练的老年人的孤独感.
有氧健身成为减轻受研究人口中孤独风险的最重要因素.

关键词:

衰老的衰老衰老的衰老人工智能的人工智能是人工智能.心脏呼吸系统的健康状况心理健康心理健康人们的生活质量.福利 - - 幸福的感觉

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