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社会评估决策的计算建模阐明了青少年焦虑的个体差异
Peter J Castagna1, Elizabeth V Edgar2, Raphaëlle Delpech2
1Department of Psychology, The University of Alabama, Tuscaloosa, Alabama, USA.
概括
对社会判断任务的计算建模显示,决策值参数预测了青少年的焦虑症状. 这种方法为理解心理病理学中的个人差异提供了一种新的方法.
科学领域:
- 认知神经科学 认知神经科学
- 发展心理学 发展心理学
- 计算精神病学是一种计算精神病学.
背景情况:
- 青春期涉及对社会线索的高度敏感性,特别是同龄人的拒绝,这可能会加剧社会焦虑.
- 社会评估决策任务揭示了信息处理偏差的神经相关性,但将表现与精神病理联系起来具有挑战性.
研究的目的:
- 调查漂移扩散建模在社会判断范式 (SJP) 上分解性能中的实用性.
- 确定计算机建模是否可以识别青少年焦虑症状,青春期,年龄和性别的个体差异.
主要方法:
- 一个由103名青少年组成的样本完成了SJP和焦虑和青春期的自我报告措施.
- 应用漂移扩散建模来分析SJP性能,重点关注决策值参数.
主要成果:
- 决策值参数显著预测了青少年自我报告的焦虑.
- 这种预测关系即使在考虑标准SJP绩效指标时也仍然显著.
结论:
- 使用计算建模分析任务性能,特别是决策值,可以揭示青少年焦虑的个体差异.
- 这种方法有望在社会判断任务中发现基于绩效的个人差异.
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