基于机器学习方法的自闭症谱系障碍儿童自闭症行为检查清单中的差异性项目的功能
Kanglong Peng1, Meng Chen2, Libing Zhou2
1Rehabilitation Department, Shenzhen Children's Hospital, Shenzhen, China.
Frontiers in psychiatry
|October 1, 2024
概括
自闭症行为检查清单 (ABC) 显示了可靠的心理测量特性,用于评估自闭症谱系障碍 (ASD) 症状. 然而,年龄,性别和症状类型可以影响结果,需要仔细解释.
科学领域:
- 心理测量 心理测量 心理测量
- 发展心理学 发展心理学
- 临床心理学 临床心理学
背景情况:
- 自闭症谱系障碍 (ASD) 诊断依赖于行为评估.
- 自闭症行为检查清单 (ABC) 是评估自闭症症状的常用工具.
- 了解评估工具的心理测量特性对于准确的诊断至关重要.
研究的目的:
- 评估自闭症行为检查清单 (ABC) 在患有自闭症儿童的心理特征.
- 用拉什分析来评估ABC的可靠性和有效性.
- 在ABC中调查差异性项目功能 (DIF).
主要方法:
- 拉什分析被用来检查ABC的心理特征.
- 这项研究包括3319名被诊断为ASD的儿童.
- 使用LASSO (GPCMlasso) 的通用部分信用模型来检测DIF.
主要成果:
- 该ABC证明了可接受的适应Rasch模型,支持其单维性.
- 在所有ABC项目中确定了无序类别函数和DIF.
- 响应模式因自闭症特征,年龄,性别和症状分类而异.
结论:
- 拉什分析提供了证据,证明ABC能够准确地反映ASD症状.
- 人口特征,如年龄和性别,可以引入评估偏见.
- 对ABC结果的临床解释需要考虑人口和临床因素,以避免诊断偏差.
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