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Objective: To identify what online patient information (presented in English) is available to parents about prenatal microarray (CMA) and exome sequencing (ES), and evaluate its content, quality, and readability. Method: Systematic searches (Google and Bing) were conducted, and websites were categorised according to their purpose. Websites categorised as patient information were included if they were: in English, directed at patients, or were a text, video, or online version of an information leaflet. Author‐developed content checklists, the DISCERN Genetics tool, and readability tests (the Flesch Reading Ease Score, the Gunning Fog Index, and the Simple Measure of Gobbledygook Index) were then used to assess those sources of patient information. Results: Of the 665 websites screened, 18 met the criteria. A further 8 sources were found through a targeted search of professional organisations, resulting in 26 sources available for further evaluation. In general, this was found to be low in quality, omitted details recommended by national or international guidance, and was written at a level too advanced for average readers. Conclusion: Improvements should be made to the content, quality, and readability of online information so that it both reinforces and complements the discussions between parents and clinicians about testing options during pregnancy. Key points: What's already known about this topic? The Internet is an important source of information for parents during pregnancyLittle is known about the availability and standard of online information about newer prenatal genetic tests like chromosomal microarray (CMA) and prenatal exome sequencing (ES) What does this study add?Our results revealed limited online information aimed at parents about CMA and ESThe information we did identify was lacking the details recommended by professional guidelines, had low quality scores, and was written at an advanced levelImprovements to online information for parents are needed to support informed decision‐making regarding prenatal genetic tests [ABSTRACT FROM AUTHOR]

By the end of their first year, infants can interpret many different types of complex dynamic visual events, such as caused-motion, chasing, and goal-directed action. Infants of this age are also in the early stages of vocabulary development, producing their first words at around 12 months. The present work examined whether there are meaningful individual differences in infants' ability to represent dynamic causal events in visual scenes, and whether these differences influence vocabulary development. As part of the longitudinal Language 0–5 Project, 78 10-month-old infants were tested on their ability to interpret three dynamic motion events, involving (a) caused-motion, (b) chasing behaviour, and (c) goal-directed movement. Planned analyses found that infants showed evidence of understanding the first two event types, but not the third. Looking behaviour in each task was not meaningfully related to vocabulary development, nor were there any correlations between the tasks. The results of additional exploratory analyses and simulations suggested that the infants' understanding of each event may not be predictive of their vocabulary development, and that looking times in these tasks may not be reliably capturing any meaningful individual differences in their knowledge. This raises questions about how to convert experimental group designs to individual differences measures, and how to interpret infant looking time behaviour. [ABSTRACT FROM AUTHOR]

A long‐standing question in child language research concerns how children achieve mature syntactic knowledge in the face of a complex linguistic environment. A widely accepted view is that this process involves extracting distributional regularities from the environment in a manner that is incidental and happens, for the most part, without the learner's awareness. In this way, the debate speaks to two associated but separate literatures in language acquisition: statistical learning and implicit learning. Both fields have explored this issue in some depth but, at present, neither the results from the infant studies used by the statistical learning literature nor the artificial grammar learning tasks studies from the implicit learning literature can be used to fully explain how children's syntax becomes adult‐like. In this work, we consider an alternative explanation—that children use error‐based learning to become mature syntax users. We discuss this proposal in the light of the behavioral findings from structural priming studies and the computational findings from Chang, Dell, and Bock's (2006) dual‐path model, which incorporates properties from both statistical and implicit learning, and offers an explanation for syntax learning and structural priming using a common error‐based learning mechanism. We then turn our attention to future directions for the field, here suggesting how structural priming might inform the statistical learning and implicit learning literature on the nature of the learning mechanism. In this article, Peter and Rowland explore the role of implicit statistical learning in syntactic development. It is often accepted that the processes observed in classic implicit learning or statistical learning experiments play an important role in the acquisition of natural language syntax. As Peter and Rowland point out, however, the results from neither research strand can be used to fully explain how children's syntax becomes adult‐like. They propose to address this shortcoming by using the structural priming paradigm. [ABSTRACT FROM AUTHOR]

Presents a study which investigated the utility of the Early Screening Profiles to differentiate between preschoolers at risk for cognitive delays and non-risk preschoolers. Methods; Results; Discussion.

A strong predictor of children's language is performance on non‐word repetition (NWR) tasks. However, the basis of this relationship remains unknown. Some suggest that NWR tasks measure phonological working memory, which then affects language growth. Others argue that children's knowledge of language/language experience affects NWR performance. A complicating factor is that most studies focus on school‐aged children, who have already mastered key language skills. Here, we present a new NWR task for English‐learning 2‐year‐olds, use it to assess the effect of NWR performance on concurrent and later vocabulary development, and compare the children's performance with that of an experience‐based computational model (CLASSIC). The new NWR task produced reliable results; replicating wordlikeness effects, word‐length effects, and the relationship with concurrent and later language ability we see in older children. The model also simulated all effects, suggesting that the relationship between vocabulary and NWR performance can be explained by language experience‐/knowledge‐based theories. [ABSTRACT FROM AUTHOR]

Background: Previous studies have suggested differences in multiple sclerosis (MS) severity according to ethnicity., Methods: Data were obtained from the UK MS Register, a prospective longitudinal cohort study of persons with MS. We examined the association between self-reported ethnic background and age at onset, symptom of onset and a variety of participant-reported severity measures. We used adjusted multivariable linear regression models to explore the association between ethnicity and impact of MS, and Cox proportional hazards models to assess disability progression., Results: We analysed data from 17,314 people with MS, including participants from self-reported Black ( n = 157) or South Asian ( n = 230) ethnic backgrounds. Age at MS onset and diagnosis was lower in those of South Asian (median 30.0) and Black (median 33.0) ethnicity compared with White ethnicity (median 35.0). In participants with online MS severity measures available, we found no statistically significant evidence for an association between ethnic background and physical disability in MS in both cross-sectional and longitudinal analyses., Conclusion: We found no association between ethnic background and MS severity in a large, diverse UK cohort. These findings suggest that other factors, such as socioeconomic status and structural inequalities, may explain previous findings., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.