小儿心理健康风险计算器的发展基础 幼儿心理健康风险计算器
Leigha A MacNeill1, Yudong Zhang2, Gina M Giase2
1Department of Human Development and Family Science, Purdue University, 1202 Mitch Daniels Blvd., West Lafayette, IN 47907; Institute for Innovations in Developmental Sciences, Northwestern University, 625 N. Michigan Ave., Chicago, IL 60611.
Academic pediatrics
|August 18, 2025
概括
这项研究验证了DECIDE早期儿童心理健康风险算法,并发现儿童和家长的优势可以改善预测,支持幼儿的公平心理健康护理.
科学领域:
- 儿科心理健康 儿科心理健康
- 风险预测算法 风险预测算法
- 儿童心理学 儿童心理学
背景情况:
- 早期发现幼儿的心理健康问题对于及时干预至关重要.
- 现有的风险计算器需要验证和改进,以获得更广泛的临床实用性.
- 基于优势的方法可以减轻风险评估中的偏见.
研究的目的:
- 复制和验证DECIDE早期儿童心理健康风险算法.
- 评估儿童和家长资产的预测附加值.
- 推进基于优势的框架,用于公平的风险识别.
主要方法:
- 利用了家庭未来和儿童福祉研究 (N=2,763) 和心理健康,早期合成队列研究 (N=323) 的数据.
- 应用流行病学风险预测方法来复制DECIDE算法 (人口统计,易怒,不良童年经历).
- 研究了使用曲线下的面积 (AUC) 和综合歧视改进 (IDI) 的儿童和育儿资产的预测效用.
主要成果:
- 在这两项研究中,DECIDE算法都成功复制了 (AUC=.70).
- 儿童资产在两个队列中都表现出超出了DECIDE算法的预测效用.
- 育儿资产在未来家庭和儿童福祉研究中也显示出预测效用.
结论:
- 对风险预测算法的强有力的验证确保了概括性和临床实用性.
- 将基于优势的方法集成到心理健康风险算法中,可以促进公平的识别.
- 这项研究为在儿科护理中实施早期心理健康决策工具提供了基础.
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