多样性意识的人口模型:在ABCD队列中量化社会空间因素与认知发展之间的关联
Nicole Osayande1,2, Justin Marotta1,2, Shambhavi Aggarwal1,2
1McConnell Brain Imaging Centre, Montreal Neurological Institute (MNI), McGill University, Montreal, Quebec, Canada.
Research square
|August 16, 2024
概括
意识到多样性的人口模型对于了解不同群体的社会经济和认知发展至关重要. 这些模型揭示了种族和地理位置如何影响认知结果,特别是少数民族儿童,解决当前方法的局限性.
科学领域:
- 人口神经科学 人口神经科学
- 发展心理学是发展心理学.
- 量化社会科学 量化社会科学
背景情况:
- 人口层面的分析面临着混因素和对代表性不足的群体有限的概括性的挑战.
- 现有的方法往往缺乏定量技术来解决人口分层问题,阻碍了整体的见解.
- 像青少年大脑认知发展 (ABCD) 研究这样的大规模队列提供了研究神经行为和社会人口关系的机会.
研究的目的:
- 提出和验证一个意识到多样性的人口建模框架,以系统地纳入多样化的属性.
- 阐明社会经济地位 (SES) 与认知发展之间的关系中的个人间差异.
- 为了解决捕捉人口分层的定量技术的差距.
主要方法:
- 借助贝叶斯的多层回归和分层后.
- 建造了14个不同的截止点和不同的斜率模型.
- 在美国17个州和5个种族小组中调查了3种认知表型和5种社会人口统计变量.
主要成果:
- 社会人口学变量表现出系统的社会空间效应,导致认知结果的变化.
- 低的SES不成比例地影响了黑人和西班牙裔儿童的认知发展;高的SES受益于白人和亚洲儿童 (少数群体减少回报理论).
- 易受逆境影响的子组与流体认知比结晶认知有更强的关联.
- 后分层化纠正了群体归因偏差,揭示了ABCD研究中的采样差异.
结论:
- 多样性意识的人口模型对于跨领域的精确和可解释的见解至关重要.
- 这项研究强调了美国种族与地理位置之间的联系.
- 模型必须考虑社会的交叉组成,以获得全面的理解.
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