评估自我调节学习结构中的时间动态作为参与数字健康干预的预测因素
Claudia Liu1, Matthew Fuller-Tyszkiewicz2, Jake Linardon2
1School of Psychology, Deakin University.
Behavior therapy
|February 25, 2026
概括
当自我调节学习 (SRL) 随着时间的推移而被衡量时,参与数字健康干预 (DHIs) 的情况会有所改善. 后来的SRL评估比DHI试验中的基线措施更好地预测用户参与.
科学领域:
- 数字健康干预措施 数字健康干预措施
- 行为科学 行为科学
- 心理学 心理学 心理学
背景情况:
- 数字健康干预措施 (DHIs) 显示出希望,但在用户参与方面存在困难.
- 之前的参与预测指标显示效果大小小小,不一致.
- 参与预测指标通常仅在基线评估,忽视时间波动.
研究的目的:
- 在DHI中调查自我调节学习 (SRL) 的时间变化.
- 为了确定改变SRL是否预测了与辩证行为疗法DHI的参与.
- 在6周的试验中,评估SRL在不同时间点的预测能力.
主要方法:
- 一项为期6周的辩证行为疗法 (DHI) 随机对照试验.
- 有113名经常暴饮暴食的成年人参与了这项研究.
- 对自我调节学习 (SRL) 变量和参与度指标 (模块,评估,技能活动) 的纵向分析.
主要成果:
- 观察到SRL变量的显著时间变化,主要是在个体内.
- 在6周的时间里,SRL对参与结果的预测能力有所增加.
- 后来的SRL测量比基线测量更强有力的参与预测.
结论:
- 自律学习 (SRL) 在使用数字健康干预期间波动很大.
- 动态的,SRL的个人评估提高了用户参与的预测.
- 未来的DHI研究应该纳入参与的时间动态及其预测因素.
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