MARCO GENERAL INTERNACIONAL. Principales declaraciones y resoluciones

As an extensive discussion of the relevant literature has already been presented and discussed in Chapters 1 and 2, the introduction section within this chapter, and proceeding research-based chapters, will not repeat these discussions. It will instead

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reiterate the key areas of literature and theoretical arguments as relevant to the current chapter’s specific research within the introduction section and will place core focus on the relevance of these to the current research being discussed. In particular, the importance of exploring the possibility of a screening measure for pre-reading age children will be discussed here.

The current research chapter offers a cross-sectional perspective on understanding various aspects of developmental dyslexia in primary-aged children across three schools located within different socioeconomic environments. This study aimed to investigate the practical value of the novel tool, the DtD task, as a measure of skills compromised in some individuals at risk of developmental dyslexia. The performance on the DtD task and other already established tests associated with core deficits of dyslexia, such as phonological processing, memory and rapid naming was assessed. These three measures have been previously shown to be good predictors of dyslexia (Hulme & Snowling, 2009; Vellution et al., 2004). Reasoning abilities were also included within the test battery. The investigation of differences in DtD performance between children at high, medium and low risk of dyslexia was a crucial part of this study.

As the DtD software generates various measures (Chapter 3 provides details), which putatively reflect different skills, it is imperative to investigate which measures from this tool may be related to dyslexia-sensitive and intelligence tests. Thanks to this, it will be possible to evaluate the type of skills associated with the DtD test. This will help to verify empirically whether children performing poorly on the DtD test also show difficulties in motor, phonological, memory and/or cognitive tasks.

As discussed in Chapter 1, the role of intelligence in dyslexia has been long debated in the literature, and the classical definition of dyslexia included an IQ - reading level discrepancy. This means that a child with dyslexia would have to have a reading level significantly lower than the level expected of their intelligence (BPS, 1999). However, research has since shown that children who would fit into this IQ – reading level discrepancy category and those who would not, do not differ qualitatively (Carroll et al., 2016; Share & Shalev, 2004; Stanovich & Siegel, 1994). The current study will also provide an opportunity to examine reasoning levels of children at risk

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of dyslexia to see if those at high risk perform poorer on these tasks. However, the discrepancy definition will not be used in the current study.

The present study involves an unselected sample of children. This provides a more representative sample than has been used in most previous studies in this area. Previous studies have tended to use sets of children at familial risk of dyslexia and matched control groups (e.g., Kevan & Pammer, 2009) or have excluded borderline cases (Le Jan et al., 2011). However, such an approach is prone to sampling biases as recruitment of risk families differs across studies: for example, some use children who have at least one parent with dyslexia, and others recruit children with dyslexic siblings. Often, this is based on self-report of family members; parents’ awareness of dyslexia may also be related to more motivated volunteers taking part in studies. Therefore, the choice of an unselected sample may minimize these biases which will strengthen the validity of results.

Similarly, the existent literature is unable to provide a clear picture of gender differences in those with developmental dyslexia. Although many studies have reported that males tend to be identified with dyslexia more often than females (e.g., Rutter et al., 2004), others point out that it may depend on who conducts the assessment, and that boys may be more likely to receive a diagnosis due to their misbehaving (Shaywitz, 1996). To address this gap in understanding, the current research will explore performance on the tasks and dyslexia risk across genders.

Previous research has further indicated that low socioeconomic status may be linked to poor phonological awareness (Nittrouer, 1996). It has been shown that children from families with higher socioeconomic status, with access to more resources and educated parents, tend to outperform other children (Buchmann & Hannum, 2001) and are less likely to develop reading difficulties (Chaney, 2008; Whitehurst & Lonigan, 1998). A more detailed discussion on the impact of SES on reading abilities and disabilities was provided in Chapter 1. The current study’s sample comprises children attending three different primary schools, associated with different socioeconomic backgrounds. The purpose of including children from different backgrounds was to assure the representativeness of the sample. However, it also provided an opportunity to explore differences in performance among children

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attending different schools. The present study also focuses on primary school aged children in three different age cohorts as already discussed in Chapter 3. The youngest cohort comprises pre-reading children, which minimizes the reciprocal effect of reading on related cognitive skills (Castles & Coltheart, 2004). The inclusion of children who have not experienced formal reading instructions and were not explicitly exposed to reading is crucial as deficits present in these children could be interpreted as causal to reading problems. An investigation of such pre-reading cohorts’ deficits minimises internal validity concerns as, in opposition to deficits found in older children, they cannot be seen as a consequence of poor reading instruction or lack of practice.

Currently, there is a good understanding within the filed that phonological processing deficits are key in dyslexia (Snowling, 2000). However, these may be seen as proximal causes of reading problems, with cerebellar (Fawcett et al., 1996) and visual pathways deficits (Stein, 2001) seen as distal, brain-based, underlying explanations. It is argued that if these deficits underlie developmental dyslexia, they should be apparent in children even before they learn to read. This assumption provides a great opportunity to develop a screening tool that would measure motor and visual processes that could predict reading but are not related to phonological and language knowledge. This is of particular importance as often the formal identification of reading problems occurs late (Singleton, 2009). Late identification leads to late interventions and is often related to a negative cycle of educational and life achievement (Stanovich, 1986). The identification of dyslexia is particularly difficult in EAL children for whom assessments designed for English native speakers are not appropriate (Everatt et al., 2004).

Non-linguistic screening tasks do currently exist however they are never used as stand-alone tests and they present a number of challenges. Two such tests are part of the DEST/DST/DAST screening batteries by the Sheffield group. These are Bead Threading (also used in the current study) and postural stability tests. Although studies fairly consistently show significant differences in performance on these tasks between dyslexic and control groups (Fawcett et al., 1996; Ramus et al., 2003), such tasks generally appear poor at predicting reading performance (Simpson & Everatt, 2005). This possibly indicates that such tasks are not a good proxy for cerebellum

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function. Similarly, psychophysical tasks associated to visual pathways processing tend to be controversial and their construct validity has been questioned (Skottun, 2013). Also, some of the tasks require specialized, not portable and expensive equipment (e.g., Goulème, Villeneuve, Gérard, & Bucci, 2017; Kevan & Pammer, 2009). Furthermore, none of the existing tests measure a combination of skills believed to be compromised in dyslexia. The novel dot-to-dot task has a potential to address some of these issues. It is easy to use and requires relatively inexpensive equipment (laptop and a graphics tablet). It only takes up to ten minutes to complete the task. The DtD task presumably involves a broad range of motor, visual, and attentional skills; it requires no phonological processing and minimal language reasoning (to understand instructions).

4.1.1 Research aims and hypotheses

This study aimed to investigate whether performance on the DtD task can reliably distinguish between those children who were at high, medium or low risk of dyslexia as assessed by an existing screening tool – the Lucid Rapid (see Chapter 3 for details). As the DtD is a new test under investigation, it was important to investigate which of its measures, if any, were related to children’s performance on dyslexia sensitive and reasoning tests. Differences in the range of dyslexia-sensitive and reasoning tests between different risk groups were investigated, and school and gender effects were also explored.

The following hypotheses were formulated:

(1) Performance on the DtD task, the established dyslexia screening tests, and verbal (Similarities) and non-verbal reasoning (Matrix Reasoning and Block Design) tests will significantly differ between children at high, medium and low risk of dyslexia as assessed by Lucid Rapid.

(2) Performance on the DtD task will be related to the performance on some of the dyslexia-sensitive tasks (Phonological Processing, RAN, memory and motor tasks), to motor task and to verbal and non-verbal reasoning.

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It was also aimed to examine whether school (socioeconomic background) and gender had any effect on children’s performance on dyslexia screening tests, reasoning tests and the DtD task.

4.2 Methods