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身体活动意图-行为差距的心理和技术预测因素:一个可解释的机器学习分析分析

Yirong Li¹, Jianguang Cai¹

¹School of Physical Education, Hunan University of Science and Technology, Xiangtan, China.

Frontiers in psychology

|October 13, 2025

概括

弥合身体活动意图与行为之间的差距需要理解心理因素. 自我有效性和感知到的障碍是关键,智能工具发挥了支持作用.

科学领域:

行为科学行为科学
健康心理学心理健康心理学
技术的接受技术的接受

背景情况:

身体活动 (PA) 的意图往往无法转化为实际行为,造成了显著的意图-行为 (I-B) 差距.
了解这种差距的调节者对于开发有效的干预措施至关重要.
现有的研究往往使用二分法度量,限制对IB差距大小的细微理解.

研究的目的:

整合心理和技术框架来研究缓解体育活动意图-行为差距的机制.
开发一种使用基线校正的标准化,连续测量PA I-B差距.
确定影响PA I-B差距的关键预测因素及其非线性相互作用.

主要方法:

在对1334名中国成年人的调查数据上使用了机器学习框架 (XGBoost).
结合了健康信念模型和技术接受和使用的统一理论.
为了连续测量PA I-B差距,利用了基线校正.

主要成果:

XGBoost模型 (R2=0.647) 的表现优于传统的回归,识别感知障碍,自我效能,使用智能工具的意图和社会支持作为核心预测因素.
更高的感知障碍和深夜活动扩大了差距;更大的自我效能,感知好处,使用智能工具的意图,社会支持,社会影响力和创新缩小了差距.
心理认知是一个比智能体育工具更强大的预测器,智能体育工具作为辅助资源.

结论:

心理认知和智能工具共同影响PA I-B差距.
自我效能和感知到的障碍是关键的心理因素.
未来的研究应该利用纵向设计和客观数据进行因果推断.

关键词:

卫生信仰模型 (HBM)SHAP可解释的方法方法双重机器学习是机器学习.意图与行为之间的差距.身体活动身体活动技术接受和使用的统一理论 (UTAUT)

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