学前和青春期前的外部化问题的先例:一种机器学习方法
1Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai, 200062, China.
母亲因素是学前外部化问题的关键预测因素,而母子关系动态在青春期前变得最重要. 干预措施应适应这些发展阶段.
科学领域:
- 儿童心理学 儿童心理学
- 发展心理学 发展心理学
- 机器学习在行为科学中的应用
背景情况:
- 外化问题是儿童发育的一个重要问题.
- 了解外化问题的发展轨迹和预测因素对于及时干预至关重要.
- 之前的研究已经探讨了各种风险因素,但需要对不同发育阶段的预测因素进行数据驱动的比较.
研究的目的:
- 识别和比较儿童,母亲和母亲-儿童双层特征在预测学前和青春期外化问题的相对重要性.
- 使用机器学习方法来发现复杂的预测模式.
- 为外化问题提供发展敏感干预措施的发展信息.
主要方法:
- 这是一项纵向研究,涉及1364个母婴二合体.
- 通过母亲报告和在学前和青春期的直接观察收集数据.
- 应用随机森林算法用于预测建模.
主要成果:
- 对外部化问题的预测模型在学龄前和青春期前有显著差异.
- 在学前教育中,母亲的特征 (抑郁症状,教育,敏感性) 是最强的预测因素,其次是二极因素.
- 在青春期前,母子双向特征 (冲突,积极关系) 成为主要预测因素,而母亲因素则起到次要作用.
- 儿童的消极反应性是青春期前的一个显著的预测因素,而儿童的特征在两个阶段普遍影响较小.
结论:
- 母亲特征在幼儿时期是预测外部化问题的核心,在青春期前转向母婴双向动态.
- 干预措施应适合发展:学前教育计划应侧重于母亲的福祉和早期的关系基础.
- 青春期前的干预应优先加强母婴关系,并应对两种挑战,以减轻外部化问题.
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