人工智能驱动的医疗保健平台上互联网适应性和使用行为之间的纵向关系:一个交叉滞后的面板网络分析
1College of Business Administration, Capital University of Economics and Business, Beijing, 100070, China.
Acta psychologica
|February 8, 2026
概括
用户的互联网适应性显著影响人工智能医疗平台的使用,诸如自我效能和疾病预防等因素随着时间的推移变得至关重要. 这种适应驱动了诸如自我诊断和健康预防等领域的参与.
科学领域:
- 数字健康数字健康
- 人与计算机的交互
- 医疗保健中的人工智能
背景情况:
- 互联网的适应性对于人工智能医疗平台在数字健康转型中的成功至关重要.
- 了解用户适应性和平台使用之间的动态相互作用是必不可少的,但仍然不清楚.
研究的目的:
- 研究用户互联网适应性和AI医疗保健平台上的使用行为的网络结构和动态交互机制.
- 发现随着时间的推移适应性和使用之间的共同进化模式.
主要方法:
- 采用多波纵向设计的交叉延迟面板网络 (CLPN) 分析.
- 分析了网络结构和适应性和使用行为之间的因果关系.
主要成果:
- 网络结构从分散发展到集中,以自我有效性和疾病预防为关键节点.
- 互联网适应性因素 (信息保护,学习能力,自我控制) 积极预测人工智能医疗平台的使用 (自我诊断,疾病预防).
- 观察到的性别差异:女性表现出整体处理,男性表现出功能性使用模式.
结论:
- 用户的互联网适应性是人工智能医疗平台参与的重要预测因素,从适应到使用建立起因果关系.
- 个性化的平台设计和服务可以通过了解用户行为演变和性别特定的交互模式来获取信息.
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