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:
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 --
中文摘要
维多利亚研究中的早期语言分析。大约7.5%的儿童有语言发展困难,并有终身的后果,并有发展性语言障碍。及早识别和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困难的儿童有持续的困难,哪些会解决。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,但这些解释的方差很小。小规模的研究已经确定,早期的个体差异在语言学,认知和/或社会认知因素可能预测语言轨迹。然而,由于有限的后续行动,样本量,和有限的措施,研究结果仍然模棱两可。严格检查早期个体差异的语言学,认知和社会认知因素和预测语言轨迹需要详细的实证数据,早期语言在维多利亚研究(ELVS),纵向社区队列(N=1,910)专注于语言,使用ELVS的数据,我将进行描述性,回归和潜在类分析,以确定:(1)语言轨迹和儿童的比例与持续,解决和迟发性困难;(2)在多大程度上语言,认知和社会认知因素预测轨迹;(3)不同的轨迹如何预测以后的教育和识字结果;(4)在早期语言,认知和社会认知的分类集群/亚组是否可能,以及这些如何预测以后的语言,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,从而制定政策和实践,并为语言障碍的个体发生理论提供信息。
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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