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Understanding the linguistic, cognitive, and socio-cognitive predictors of differing trajectories in child language development:

Understanding the linguistic, cognitive, and socio-cognitive predictors of differing trajectories in child language development:
了解儿童语言发展不同轨迹的语言、认知和社会认知预测因素:
批准号:
2538869
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --

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中文摘要
翻译
大约7.5%的儿童在语言发育方面有困难,会导致终生后果,并患有发育性语言障碍。及早查明并提供有效的干预措施可有助于减少这些困难的影响。然而,幼儿语言的波动性使得很难预测哪些早期语言障碍的儿童存在持续性困难,哪些会得到解决。流行病学研究已经确定了语言轨迹和结果的多个预测因素,但这些因素几乎解释不了这种差异。小规模研究发现,早期个体在语言症状、认知和/或社会认知因素上的差异可能会预测语言轨迹。然而,由于跟进、样本量和测量方法的限制,研究结果仍然不明确。为了严格检验语言症状学、认知和社会认知因素的早期个体差异并预测语言轨迹需要详细的实证数据,维多利亚早期语言研究(ELVS)提供了独特的这一点,该研究是一个专注于语言的纵向社区队列(N=1,910)。利用ELVS数据,我将进行描述性、回归和潜在类别分析,以确定:(1)语言轨迹和具有持续性、解决性和后发性困难的儿童的比例;(2)语言、认知和社会认知因素在多大程度上预测轨迹;(3)不同的轨迹如何预测未来的教育和识字结果;(4)是否可以在早期的语言、认知和社会认知症状学中对集群/亚群进行分类,以及这些因素如何预测后来的语言、教育和识字结果?在回答这些问题时,我的目标是提供与早期识别相关的发现,从而提供政策和实践,并为语言障碍的个体发生学理论提供信息。
英文摘要
Analyses of the Early Language in Victoria Study.Approximately 7.5% of children have difficulties with language development with lifelong consequences and have Developmental Language Disorder. Early identification and provision of effective intervention could help to reduce the impact of these difficulties. However, volatility in young children's language makes it hard to predict which children with early language difficulties have persisting difficulties and which will resolve.Epidemiological studies have identified multiple predictors of language trajectories and outcomes, but these explain little of the variance. Small-scale studies have identified that early individual differences in linguistic symptomatology, cognitive, and/or socio-cognitive factors may predict language trajectories. However, due to limited follow-up, sample size, and restricted measures, the study findings remain equivocal.To rigorously examine early individual differences in linguistic symptomatology, cognitive, and socio-cognitive factors and predict language trajectories requires detailed empirical data, the Early Language in Victoria Study (ELVS), a longitudinal community cohort (N=1,910) focusing on language, uniquely provides this.Using the ELVS data, I will conduct descriptive, regression, and latent class analyses to identify: (1) language trajectories and the proportion of children with persisting, resolving, and late-emerging difficulties; (2) to what degree linguistic, cognitive, and socio-cognitive factors predict trajectories; (3) how differing trajectories predict later educational and literacy outcomes; (4) whether categorising clusters/subgroups in early linguistic, cognitive, and socio-cognitive symptomatology is possible and how do these predict later language, educational, and literacy outcomes?In answering these questions, I aim to deliver findings relevant to early identification, and therefore policy and practice, and inform theories of the ontogeny of language disorders.
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