The Association Between Visual, Nonverbal Cognitive Abilities and Speech, Phonological Processing, Vocabulary and Reading Outcomes in Children With Cochlear Implants Lindsey Edwards and Sara Anderson Objective: The aim of this study was to explore the possibility that specific nonverbal, visual cognitive abilities may be associated with outcomes after pediatric cochlear implantation. The study therefore examined the relationship between visual sequential memory span and visual sequential reasoning ability, and a range of speech, phonological processing, vocabulary knowledge, and reading outcomes in children with cochlear implants.

deafness, including global developmental delay, cerebral palsy or autistic spectrum disorder, which may be known preimplantation (e.g., Meinzen-Derr et al. 2010). However, many additional difficulties that are not apparent before the child has received cochlear implants, are more subtle, or emerge gradually as the child matures. For example, specific learning disabilities such as language disorders or dyslexia cannot be identified in very young deaf children; their diagnosis is typically not achieved until much later than in hearing children. To add to the complexity, some children make poor progress in developing speech, language and literacy skills after cochlear implantation for no readily identifiable reason. In this case factors such as the nature of the child’s language-learning environment and parent/carer interactions with the child are likely to be contributory factors. Thus there is a pressing need to improve our knowledge and understanding of the factors that are predictive of outcome or benefit, and translate these into individualized assessment and intervention strategies to achieve optimal cognitive and linguistic development. One area of research that is showing considerable promise in meeting this need has focused on describing, understanding, and explaining the neurocognitive or information-processing variables that contribute to individual differences in outcomes and benefit (e.g., Fagan et al. 2007; Pisoni, et al. 2010). Furthermore, as Pisoni et al. (2008) state “while some proportion of the variance in performance is associated with peripheral factors related to the audibility and the initial sensory encoding of the speech signal into information-bearing sensory channels in the auditory nerve, several additional sources of variance are associated with more central cognitive and linguistic factors that are related to perception, attention, learning, memory and cognitive control.” Some further clues as to the cognitive processes that may be relevant in accounting for the variability in speech, language, and literacy outcomes can be drawn from a range of related lines of research, which will now be briefly considered.

Design: A cross-sectional, correlational design was used. Sixty-six children aged 5 to 12 years completed tests of visual memory span and visual sequential reasoning, along with tests of speech intelligibility, phonological processing, vocabulary knowledge, and word reading ability (the outcome variables). Auditory memory span was also assessed, and its relationship with the other variables examined. Results: Significant, positive correlations were found between the visual memory and reasoning tests, and each of the outcome variables. A series of regression analyses then revealed that for all the outcome variables, after variance attributable to the age at implantation was accounted for, visual memory span and visual sequential reasoning ability together accounted for significantly more variance (up to 25%) in each outcome measure. Conclusions: These findings have both clinical and theoretical implications. Clinically, the findings may help improve the identification of children at risk of poor progress after implantation earlier than has been possible to date as the nonverbal tests can be administered to children as young as 2 years of age. The results may also contribute to the identification of children with specific learning or language difficulties as well as improve our ability to develop intervention strategies for individual children based on their specific cognitive processing strengths or difficulties. Theoretically, these results contribute to the growing body of knowledge about learning and development in deaf children with cochlear implants. Key words: Children, Cochlear implant, Nonverbal, Cognitive, Outcomes. (Ear & Hearing 2014;35;366–374)

INTRODUCTION All parents who choose cochlear implantation for their deaf child are informed that the degree of benefit cannot be precisely predicted. Although some factors have been reliably associated with speech and language outcomes and literacy achievements, for example, age at implantation, length of auditory deprivation, and early linguistic experience (auditory–oral versus total communication), there remains a large degree of variability in outcome (e.g., Marschark et al. 2007; Archbold et al. 2008; Geers et al. 2008; Lyxell et al. 2009). Some of this variability can be accounted for by factors such as disabilities in addition to the

Phonological Processing, Verbal Memory Capacity, and Reading in Hearing Children First, in hearing children, strong associations are found between verbal (working) memory capacity and phonological processing skills, and specific reading difficulties. Verbal memory capacity refers to the amount of information that can be stored and “manipulated” in some way, over a short period of time (i.e., seconds). Verbal memory capacity is typically assessed using a digit span task giving a measure of auditory memory span, and deficits on this and other tests of verbal

Great Ormond Street Hospital for Children, London, England, United Kingdom.

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short-term memory have consistently been found in children with specific reading disorders (e.g., Gottardo et  al. 1996; de Jong 1998; Helland & Asbjørnsen 2004; Kibby et al. 2004). One task commonly used to assess phonological processing skills is the nonword repetition task, which tests the ability to assemble, rehearse, and produce novel phonological sequences from short-term memory. A number of studies have found a strong association between deficits in nonword repetition and both specific language impairment and reading difficulties (e.g., Bishop et al. 1996; Catts et al. 2005; Conti-Ramsden & Durkin 2007; Rispens & Parigger 2010).

Phonological Processing and Reading in Deaf Children Second, in children with a hearing loss, with or without cochlear implants, phonological processing skills are typically weak compared with those of hearing peers. These skills have been associated with a range of speech, language, and literacy outcomes. For example, Dillon and Pisoni (2006) tested nonword repetition in 76 children with cochlear implants aged 7 to 9 years. They found strong associations between nonword repetition and three measures of reading outcome (nonword reading, single word reading, and reading comprehension). These correlations remained significant when age at onset of deafness, communication mode, and performance intelligence quotient (IQ) were controlled for. Carter et al. (2002) also used a nonword repetition task to examine prosodic representations of words. They found that 8- to 10-year olds, who had been using their cochlear implant for a mean of 5 years, only correctly imitated 5% of the nonwords. However, 64% of the imitations contained the correct number of syllables. They also found that the syllable score was significantly positively correlated with language comprehension and speech intelligibility. Recently, Casserly and Pisoni (2013) demonstrated that the performance of 8- to 10-year-old cochlear implant users on a nonword repetition task was predictive of measures of speech and language at the age of 16 to 18 years, including speech intelligibility, receptive vocabulary, and reading ability. In another early study Dyer et al. (2003) assessed phonological awareness and decoding skills along with rapid automatized naming of visual material, in 49 deaf students with a mean age of 13 years but whose mean reading age was 7 years. Phonological awareness and decoding skills were poorer in these deaf children compared with hearing children matched for reading (not chronological) age and correlated significantly with reading delay on the rhyme-awareness task. In addition two recent studies have also examined phonological awareness or processing skills and reading in children and adolescents with cochlear implants. Geers and Hayes (2010) reported that phonological processing skills accounted for an additional 19% of the variance in literacy achievement after factors such as sex, duration of deafness, performance IQ, and family characteristics were taken into account. Similarly, Johnson and Goswami (2010) found that reading attainment was significantly correlated with phonological awareness in 5- to 15-year olds with cochlear implants, when age and nonverbal IQ were controlled for.

Memory and Reading in Deaf Children In a third line of research (but sometimes within the same studies as described earlier in the article), the relationships between memory capacity, working memory and speech,

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language and reading skills have been explored, again both in deaf children with cochlear implants and those using conventional hearing aids. Johnson and Goswami (2010) used a forward digit span task to assess auditory memory, and the Leiter-R (Roid & Miller 1997) memory screen to assess visual memory in implanted children. They found that visual memory was not correlated with the phonological awareness tasks, but was with reading comprehension. Auditory memory was linked to phonological awareness, receptive and expressive vocabulary knowledge, reading accuracy and comprehension, along with speech intelligibility. In a longitudinal analysis with a large sample of cochlear implant users, Pisoni et al. (2011) examined the predictive relationships between auditory memory capacity (digit span) at age 8 to 9 years, and speech intelligibility, vocabulary knowledge, language ability, and reading ability at around 16 years of age. They found strong positive correlations between longest digit span at age 8 to 9 years and all the speech and language outcome measures in adolescence. However, interestingly from a theoretical perspective, backward digit span, which is considered a measure of auditory working memory (verbal memory capacity when concurrent mental processing is required) rather than simply auditory immediate memory capacity (rote sequential serial item memory), correlated significantly with tests of higher-order language functioning, but not speech perception or recognition measures. Pisoni et al. suggested that this dissociation between the forward and backward digit span results may indicate that rapid phonological encoding and immediate verbal-sequential phonological memory are essential building blocks for the development of good speech perception and speech-language skills. In addition, good verbal-sequential memory abilities are needed for all higher language processing tasks involving encoding, storing, and maintaining representations of speech sounds, spoken words, and sentence meanings in working memory.

Visual–Spatial Memory and Reading in Hearing Children While it makes intuitive sense that normal auditory–verbal memory skills are important for the effective development of spoken language and later literacy skills, it is less clear whether visual memory abilities would also be expected to play a significant role, either in hearing children or those with a hearing loss. Therefore it is perhaps unsurprising that there is considerably less research exploring this question. Thus the next piece in this puzzle is the observation that it is not only the verbal memory span that is reduced in hearing children with specific reading disability; there is evidence that their visual–spatial memory capacity or visual memory span and working memory are also poorer. The findings are less consistent than for verbal memory deficits, but the contradictory findings could be accounted for by differences in participant inclusion criteria and the nature of the memory tasks used (e.g., Olson & Datta 2002; Jeffries & Everatt 2004; Kibby et al. 2004; Smith-Spark &Fisk 2007). Menghini et al. (2011) attempted to resolve this issue by testing children with developmental dyslexia, but no other concomitant disorders and normal intelligence, and used memory tasks minimally demanding on attentional and executive cognitive resources. They concluded that children with specific reading deficits do have deficits in visual–spatial memory span, in addition to verbal memory span.

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Visual Memory and Reading in Deaf Children There is some evidence that short-term memory span for visually presented stimuli is poorer in deaf children, including those with cochlear implants, than in their hearing peers. Khan et  al. (2005) found a significant difference between deaf and hearing children in visual memory span for pictures of common objects presented in an array, where the child had to point to the pictures in the same order as that given by the examiner (Forward Memory subtest from the Leiter-R). However, there was no difference between the hearing children and children who had been using their cochlear implant for 1 year. A novel visual memory span task was developed by Cleary and colleagues based on the Simon memory game, where the task is for the child to reproduce sequences of presentations of colored lights. The authors conducted a series of experiments with children with cochlear implants and found that these children had shorter memory spans and poorer sequence learning when the same patterns were repeated, again in comparison with hearing peers (Cleary et al. 2001, 2000; Pisoni & Cleary 2004). These authors suggest that individual differences in outcome in deaf children who receive cochlear implants “may reflect fundamental learning processes that affect the encoding and retention of temporal information in both short- and long-term memory” (Pisoni et al. 2008, p. 77). Studies that report findings on visual memory span and reading ability in deaf children are equally scarce. However, two studies provide some relevant results. Harris and Moreno (2004) used pictures of objects that were visually similar, had similar sounding names, and were formed with similar hand shapes in British Sign Language or dissimilar in these three respects. Pictures were presented in increasingly long sequences, and the child had to name the objects in the order in which they had appeared. In deaf children aged 14 years (but not in the group aged 8 years), visual memory span was a significant predictor of reading performance when age and nonverbal IQ were accounted for. It is interesting to note that in these older children recall span was not affected by the similarity of the sounds of the objects’ names, suggesting the children were not using phonological coding when remembering items. Clearly, in this task although the stimuli are presented visually they are verbally encoded (as the child had to name each object), and the response mode is also verbal. Using essentially the same type of task, but with pictures of words varying in number of syllables, Kyle and Harris (2006) found no correlation between visual memory span and a number of measures including expressive vocabulary, reading, or spelling. However, these children were younger (aged 7 to 8 years), suggesting that there may be a developmental progression involved in the relative contributions of auditory compared with visual information processing in the acquisition of reading skills.

Visual Sequential Reasoning Abilities in Deaf Children The next question is whether the difficulty with auditory memory span, which relies on the processing of sequentially presented auditory information, is reflective of a wider difficulty in processing or understanding sequential information, that is, do hearing children with reading difficulties and deaf children also have problems with reasoning or problem solving with nonverbal or visual information that is sequential? To our knowledge no studies have addressed this directly in hearing or deaf children. However, Khan et  al. (2005) did report that

a group of very young (aged 2 to 5 years) deaf children performed significantly worse on the Sequential Order subtest of the Leiter-R compared with their hearing peers. To summarize, previous research has suggested that reading competence (or conversely reading deficit) is dependent on phonological processing skills, which in turn is strongly associated with verbal memory capacity, and possibly also visual memory capacity. Deaf children are at risk of experiencing significant difficulties in developing phonological awareness and processing skills, and have deficits in verbal and visual memory, as well as possibly visual reasoning problems. However, to date, no empirical studies have examined the relationships between the combination of visual memory span, visual, nonverbal reasoning skills, speech intelligibility, phonological processing, language and reading outcomes in children with a hearing loss or deaf children with cochlear implants. Given the studies described earlier in this article, it seems plausible that such a relationship may exist.

The Present Study—Aims and Rationale As outlined at the beginning of the Introduction, one of the major challenges for clinicians working with children with cochlear implants is identifying those at risk of poor progress, or those who have specific learning difficulties in addition to those arising from their deafness, as early as possible. However, most tests conventionally used to assess specific learning disorders require a minimum level of spoken language production or comprehension for their administration. This typically excludes those very children for whom the need to establish what is preventing progress is greatest. It would be of immense value if there were reliable and valid visual, nonverbal tests of neurocognitive processes that were predictive of speech, phonological processing, reading and language outcomes in children with cochlear implants, particularly if they could be administered to very young deaf children. Thus the primary aim of this study is to establish whether there are links between visual (sequential) memory span, visual sequential reasoning ability, and speech intelligibility, phonological processing, reading and vocabulary knowledge in children with cochlear implants. In this study we used phonological processing as an outcome (dependent) variable, along with reading and vocabulary knowledge (as an indicator of language TABLE 1.  Participant characteristics Male: Female Mean age at testing (SD; range) Mean age at (1st) implant (SD; range) Duration of (1st) implant use (SD; range) Etiology of deafness  Unknown  Genetic (nonsyndromal)  Syndromal  Meningitis  Rubella/cytomegalovirus infection  Meningitis Communication mode  Speech  Speech and sign  Sign

32: 34 8.5 yrs (1.9; 5.4–11.7) 3.7 yrs (1.5; 1.2–8.9) 5.13 yrs (2.0; 1.0–10.1) 39% 21% 15% 17% 6% 2% 80% 14% 6%



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development) rather than as an explanatory (independent) variable. We have focused on sequential visual cognitive processes or abilities because language is essentially sequentially based (phonemes need to be produced in the correct sequence in words, words in the right order in sentences to be grammatically correct). Therefore the ability to process sequential visual information may be hypothesized to be associated with the ability to process auditory sequential information, and thus with the development of phonological, language, and literacy abilities. There are a number of possible models of the relationships between all these factors that could be tested, for example, hierarchical models where variables are included incrementally in several steps. However, we sought to test the most simple models, and include as few variables as possible as to account for the variability in outcomes after cochlear implantation, specifically focusing on nonverbal, visual measures. This was in an attempt to maximize the clinical interpretability and value of the results. In particular, we wanted to use those tests that can potentially be administered to children before the emergence of assessable spoken language skills. However, auditory memory capacity (digit span) was also assessed and used as an explanatory variable because this test is probably the simplest auditory/ verbal one for deaf children to tackle, as it only requires the ability to articulate the numbers one to nine in a sufficiently clear manner for the examiner to be able to recognize them. Furthermore, digit span has received the most attention in previous research and it is highly established as a predictor of speech intelligibility, phonological processing ability, reading and language in implanted children. This study will therefore allow us to explore (nonstatistically) the relative strength of associations between auditory and visual memory capacities and outcomes after pediatric cochlear implantation, and consider our findings in the context of previous research. Hypothesis  •  Visual sequential reasoning and visual memory span are significantly positively associated with speech intelligibility, phonological processing, vocabulary knowledge, and reading outcomes in deaf children after cochlear implantation.

PARTICIPANTS AND METHODS Design The study used a cross-sectional, correlational design. The main explanatory variables were visual memory span and visual

sequential reasoning ability. Six outcome variables were a range of speech intelligibility, phonological processing, reading, and vocabulary knowledge measures.

Participants All the children aged between 5 and 12 years during a 6-month period, currently patients on our cochlear implant program, were invited to participate in the study. This was with the exception of children with known significant developmental delay or neuro-developmental disorders such as autistic spectrum disorder. The characteristics of the resulting sample are summarized in Table 1. The participants were 66 children, with approximately equal numbers of girls and boys. The cause of deafness was unknown for around 40% of the children, genetic (nonsyndromal) for approximately 20% and syndromal (Waardenburgs, Pendreds, CHARGE Association, Ushers syndrome and Brachio-oto-renal syndrome) in 15%, and congenital infections or meningitis in 25%. There were no significant differences in scores on any of the visual memory, visual reasoning, auditory memory, speech intelligibility, phonological processing, and vocabulary or reading tests when the children were divided into three groups according to etiology (unknown, genetic, or syndromic/infection/prematurity). All but 1 child was congenitally deaf or deafened before their second birthday. The preimplant pure-tone average aided loss for 2 and 4 kHz in the worse ear was greater than 90 dBHL. Seven children had bilateral implants: 2 simultaneously and the remainder sequentially. The majority of the children used spoken English as their main mode of communication, with some also using signs to support their communication (receptively, expressively, or in both ways). Four children had a preference for using sign expressively, but had sufficient spoken language skills to enable them to understand the instructions for the tests administered for this study. English was not the first language for the parents of 7% of the children.

Measures Memory  •  Forward Memory Subtest: Leiter International Performance Scale—Revised (Leiter-R; Roid & Miller 1997). This test assesses visual memory span by testing the child’s ability to reproduce the sequence in which the examiner has pointed to pictures of objects in a grid, presented at a rate of one picture

TABLE 2.  Descriptive statistics for the visual sequential memory and reasoning, auditory memory, speech, phonological processing, vocabulary and reading variables Normalization Sample Variable (Test) Auditory Memory Span (CMS Numbers) Fluid Reasoning composite (Leiter-R) Visual Memory Span (Leiter-R) Children’s Speech Intelligibility Measure Phonological Processing (NEPSY II) Repetition of NonWords (NEPSY II) Receptive Vocabulary (TOWK) Expressive Vocabulary (TOWK) Word Reading (WIAT-II)

Cochlear Implant Sample

Mean (SD)

Mean (SD)

Range

% of Cochlear Implant Children Lower Than 1 SD Below Norm

10 (3) 100 (15) 10 (3) N/A 10 (3) 10 (3) 10 (3) 10 (3) 100 (15)

7.17 (3.4) 104.3 (15.3) 11.9 (3.4) 69.3 (29.8) 7.61 (4.3) 10.0 (4.5) 6.8 (3.4) 7.4 (3.7) 86.5 (22.9)

1–15 67–137 2–18 0–100 1–15 1–18 3–15 3–19 40–128

56% 9% 7% N/A 34% 22% 54% 49% 43%

CMS, Children’s Memory Scale; TOWK, Test of Word Knowledge; WIAT-II, Wechsler Individual Achievement Test–II.

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per second. Again the sequences start at two stimuli in length, and become increasingly long. Testing is stopped after the child has made six errors. The number of correct sequences is converted to a scaled score (mean 10, SD 3) based on hearing children norms. The test is intended for children between 2 and 16 years of age. Numbers Forward Subtest: Children’s Memory Scale (Cohen 1997). This is a standard digit span test of verbal memory capacity, where the child repeats back increasingly long series of numbers presented one digit per second, starting with two digits. There are two trials for each sequence length, and testing is stopped once the child has failed both trials for a particular length. The number of correctly reproduced sequences is converted to an age-based scaled score. The mean and standard deviation of the hearing standardization sample are 10 and 3, respectively. The test can be used for children aged between 5 and 16 years. Visual Sequential Reasoning  •  Fluid Reasoning Composite: Leiter-R. Individual subtests from the Visualization and Reasoning battery of the Leiter-R can be combined into two separate composites labeled Fundamental Visualization and Fluid Reasoning. In this study the latter composite was used, which comprises two subtests—Sequential Order and Repeated Patterns. Sequential Order includes items such as a cat increasing in size where the child has to identify the correct next-sized cat from two possibilities. In the Repeated Patterns subtest the child has to complete patterns such as red-yellow-blue-red-yellow-?-?. Testing is stopped after seven errors for Sequential Reasoning and six errors for Repeated Patterns. Here, each subtest score is converted to a scaled score, which in turn are combined and converted to a scaled score, where the norms based on hearing children have a mean of 100 and standard deviation of 15. Children between 2 and 16 years of age can be administered this test. In the statistical analyses the Fluid Reasoning composite is referred to as the “visual sequential reasoning” variable. Speech  •  Children’s Speech Intelligibility Measure (Wilcox & Morris 1999). In this test 50 words are modeled verbally by the examiner, and the child repeats each word, which is digitally recorded. After administration of the test a judge listens to the recording and identifies the word he or she believes the child had said from a list of 12 phonetically similar possibilities. For example, for the target word “learn” the 12 possible choices are burn, churn, firm, first, germ, hurt, jerk, learn, purse, stern, term, and turn. An intelligibility rating is calculated by multiplying by 2 the total number of words the judge correctly identifies, giving a possible range of 0 to 100. This test was developed for children aged 3 years to 10 years 11 months, so some of our sample participants were older than the upper limit. However, given that the test scores are not converted to age-based standard scores, and that many of our participants might be expected to have poorer speech intelligibility than their hearing age-matched peers, it was considered acceptable to extend the age range by 1 year. The Children’s Speech Intelligibility Measure has good test–retest reliability, and inter-rater reliability on 22 randomly selected participants was found to be 0.93. Phonological Processing  •  Repetition of Nonwords Subtest: NEPSY second edition (NEPSY II; Korkman et  al. 2007). This subtest is for children aged 5 to 12 years. The child listens to a series of increasingly complex nonwords (e.g., “crumsee” through “indobtreelob” to “splinkdellblee”). The child

repeats back each word, and scores one point for each correct ­syllable. Testing is stopped after four consecutive item scores of zero. The total score is converted to a scaled score where the mean is 10 and standard deviation is 3, based on hearing children norms. Phonological Processing Subtest: NEPSY II. This subtest comprises two tasks that assess phonemic awareness. The first, the word segment recognition requires identification of words from word segments, for example, three pictures are named by the examiner—“pencil,” “window,” and “ice cream,” then the child is given the cue “indow” and asked to point to the correct picture. The second, the phonological segmentation is a test of elision where the child is asked to repeat a word and then create a new word either by omitting a syllable or a phoneme, or by substituting one phoneme in a word for another (e.g., “say ‘mistaken,’ now say it again but don’t say ‘mis’”). The child scores one for each correct response and testing is stopped after six consecutive incorrect responses. The test is for children aged 5 to 16 years and yields scaled scores where the mean is 10 and standard deviation is 3. Vocabulary Knowledge •  Expressive Vocabulary: Test of Word Knowledge (Wiig & Secord 1992). Children are shown a series of pictures and asked to either name them (if a noun such as a kangaroo) or tell the examiner what is happening (if a verb such as melting). Many of the items have more than one possible correct response. Each correct answer is given one point, testing is stopped after five consecutive errors and the total number of correct responses is converted to a scaled score (mean 10, SD 3, based on norms for hearing children). The test is for children aged between 5 and 17 years. Receptive Vocabulary: Test of Word Knowledge. Here the task is for the child to point to one picture from four possible options, which best represents the word spoken by the examiner. The words include nouns, verbs, and adjectives. Other details are the same as for the expressive vocabulary test. Reading  •  Word Reading Subtest: Wechsler Individual Achievement Test-II UK (WIAT-II UK). This test for children aged between 4 to 16 years, starts with assessing the child’s knowledge of letter names and sounds and progresses through to reading individual words of increasing difficulty. Testing is stopped after seven consecutive errors. The number of correct responses is converted to a standard score (again, mean 100, SD 15).

Procedure Ethical approval for the study was received from the National Research Ethics Service and the project complied with institution research regulatory board procedures. Parents and children were provided with written information describing the study and any questions they had regarding it were addressed before obtaining written consent from the parents. The children also gave verbal assent to participation, having been assured that their participation was voluntary and they could stop at any time should they wish. However, no child asked to stop before completion of all the tests they were able to undertake. Children implanted bilaterally were tested wearing both implants, and those who usually wore a conventional hearing aid contralaterally to their implant were tested while using it together with their cochlear implant. The children were tested individually in a clinic room at the hospital, at their school in a quiet room, or in their home,



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according to parental preference. Testing lasted a maximum of 90 min and the children were offered a break part of the way through the session. Tests were administered in the same order for each child, according to the standard procedures provided in the test manuals.

RESULTS Descriptive statistics for each of the variables (visual memory, visual reasoning, auditory memory, speech intelligibility, phonological processing, vocabulary, and reading) are presented in Table 2. These results indicate that our sample of children with cochlear implants are, on average, performing within the normal range compared with hearing children on most, but not all, of the tests. The notable exceptions, where the mean score for the sample was around 1 SD or more below the norm for hearing children, were auditory memory span, phonological processing (NEPSY II), receptive and expressive vocabulary, and word reading (WIAT-II). The percentage of children scoring 1 SD or more below the standardized mean ranged from 7 to 56% across the variables. Table  3 gives the first order, Pearson correlations between each of the variables. All the correlations were positive and statistically significant, the majority at the p < 0.001 level. To further test the associations between the visual memory span and visual sequential reasoning predictor variables and the speech intelligibility, phonological processing, vocabulary and reading composite outcome variables, a series of multiple regression analyses was performed. Three variables required logarithmic transformation to make the data normally distributed; these were receptive vocabulary, expressive vocabulary, and speech intelligibility. Two sets of analyses were then conducted, the results of which are presented in Tables 4 and 5. In both sets of analyses, in the first model only the child’s age at

implantation was entered as the independent variable. Age at implantation was chosen because previous research has found it to be the most robustly significant predictor of speech and language outcomes after pediatric implantation. It accounted for between 7 and 15% of the variance across the outcome variables. For each outcome variable, the younger the child was when they received their implant, the better their performance. In the first analysis, in the second model age at implantation was entered as the first step and then auditory memory span was added in the second step. This analysis showed that auditory memory span is highly significantly associated with outcomes after accounting for age at implantation. In the case of nonword repetition, this model accounted for 73% of the variability in scores. In the second analysis, in the first model age at implantation was again entered as the first step. In the second step, visual sequential reasoning and visual memory span were added simultaneously. Table  5 indicates that for every outcome variable, visual sequential reasoning and visual memory span together substantially increased the amount of variance accounted for, after that attributed to the child’s age at implantation. Visual sequential reasoning and visual memory span together accounted for between 16 and 25% of additional variance. In each case the increase was statistically significant at the p = 0.01 level or less. Inspection of the β coefficients reveals that for the phonological processing subtest of the NEPSY II, visual sequential reasoning was the statistically significant explanatory variable. For each of the other outcome variables, visual memory span made the significant contribution to the variance accounted for by the model.

DISCUSSION Understanding and explaining the considerable variability between individuals in outcomes after pediatric cochlear

TABLE 3.  Correlations between the visual memory, visual sequential reasoning, auditory memory, phonological processing, vocabulary and reading variables Visual Sequential Reasoning* (Leiter-R) Visual Memory Span (Leiter-R) Auditory Memory Span (CMS) Children’s Speech Intelligibility Measure Phonological Processing (NEPSY II) Repetition of Nonwords (NEPSY II) Receptive Vocabulary (TOWK) Expressive Vocabulary (TOWK) Word Reading (WIAT-II)

Visual Memory Span (Leiter-R)

Auditory Memory Span (CMS)

Children’s Speech Intelligibility Measure

Phonological Processing (NEPSY II)

Repetition of Nonwords (NEPSY II)

Receptive Vocabulary (TOWK)

Expressive Vocabulary (TOWK)

0.532 0.320

0.397

0.356

0.390

0.653

0.474

0.370

0.624

0.730

0.374

0.426

0.836

0.736

0.754

0.388

0.442

0.544

0.500

0.666

0.566

0.309

0.381

0.636

0.593

0.592

0.659

0.693

0.443

0.417

0.638

0.703

0.812

0.777

0.732

Figures in italics are significant at p = 0.05 (two-tailed). Figures in bold are significant at p = 0.01 or less (two-tailed). *Fluid Reasoning composite of the Leiter-R comprising the Sequential Order and Repeated Patterns subtests. CMS, Children’s Memory Scale; TOWK, Test of Word Knowledge; WIAT–II, Wechsler Individual Achievement Test–II.

0.723

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TABLE 4.  Regression analyses of age at implant and auditory memory span on measures of speech, phonological processing, vocabulary knowledge, and reading outcomes Phonological Processing (NEPSY II) n = 64 p

β coeff. Model 1  Age at implant   R2 Model 2  Age at implant  Auditory Memory Span   R2

Nonword Repetition (NEPSY II) n = 65

−1.093

β coeff.

0.463†

p

Expressive Vocabulary (TOWK) n = 66

p

β coeff.

p

β coeff.

Children’s Speech Intelligibility Measure n = 65

Word Reading (WIAT-II) n = 65 p

β coeff.

β coeff.

p

0.002

−0.941 0.010 0.101

−0.041 0.026 0.076

−0.046 0.011 0.097

−5.260 0.005 0.120

−0.072 0.109 0.040

0.005 0.000

−0.521 0.011 1.048 0.000 0.729†

−0.028 0.083 0.034 0.000 0.330†

−0.029 0.037 0.041 0.000 0.482†

−3.664 0.013 3.978 0.000 0.464†

−0.037 0.338 0.084 0.000 0.315†

0.148 −0.788 0.717

Receptive Vocabulary (TOWK) n = 65

Significance of the change in R2 between model 1 and model 2: *p < 0.01; †p < 0.001. TOWK, Test of Word Knowledge; WIAT–II, Wechsler Individual Achievement Test–II.

implantation is increasingly the focus of research in this field. Deaf children who receive cochlear implants, even if early in life, remain at risk of delays in developing language and literacy skills, although many do achieve these at a level comparable with that of their hearing peers. Previous research has sought to identify cognitive or information-processing factors that are associated with outcomes, but has typically focused on verbal measures such as nonword repetition, auditory–verbal memory, and verbal rehearsal speed (e.g., Dillon & Pisoni 2006; Pisoni et  al. 2010; Casserly & Pisoni 2013), rather than nonverbal visual cognitive predictors. Unfortunately, many of the tests that assess these abilities cannot be undertaken by young deaf children, especially those children with specific language or learning difficulties, as the tests rely on a basic level of spoken language understanding and production for their administration. Therefore, the primary aim of this study was to explore whether certain visual cognitive processing abilities, which can be assessed in very young deaf children before spoken language

skills emerge, are also associated with a range of speech, language, and literacy outcomes after cochlear implantation. However, before testing the primary hypothesis, it is useful to consider the context for our findings in terms of the actual outcomes achieved in our sample, and whether the associations between the speech, phonological processing, language and literacy outcomes are consistent with previous research on this issue. In our group of children aged between 5 and 12 years, who had been using a cochlear implant for between 1 and 10 years, around half of the children achieved below the normal range for hearing children (i.e., 1 SD), in their auditory memory span, and receptive and expressive vocabulary knowledge. One third or more of the children scored below the normal range on tests of word reading and phonological processing. Together these results suggest that a substantial proportion of the children have auditory–verbal memory capacity deficits and are experiencing difficulties developing the phonological processing skills that underpin the development of a wide vocabulary

TABLE 5.  Regression analyses of age at implant, visual memory span and visual sequential reasoning on measures of speech, phonological processing, vocabulary knowledge, and reading outcomes. Phonological Processing (NEPSY II) n = 64 β coeff.

p

Model 1  Age at Implant −1.093 0.002   R2 0.148 Model 2  Age at Implant −0.920 0.004  Visual Sequential 0.088 0.017  Reasoning†  Visual Memory Span† 0.254 0.109   R2 0.345†

Nonword Repetition (NEPSY II) n = 64 β coeff. −0.950

p

0.010 0.102

−0.848 0.044

0.013 0.260

0.454 0.010 0.293*

†These variables were entered into the regression model simultaneously. Significance of the change in R2 between model 1 and model 2: *p < 0.01; †p < 0.001.

Receptive Vocabulary (TOWK) n = 64 β coeff.

p

Expressive Vocabulary (TOWK) n = 65 β coeff.

−0.043 0.083

0.021

−0.048

−0.038 0.002

0.021 0.320

−0.044 0.002

0.028 0.001 0.327†

p

0.008 0.107 0.010 0.407

0.022 0.014 0.266*

Children’s Speech Intelligibility Measure n = 64

Word Reading (WIAT-II) n = 64 β coeff. −5.460

p

0.003 0.130

−4.749 0.337

0.005 0.085

1.988 0.021 0.332†

β coeff.

p

−0.074 0.103 0.042 −0.075 −0.003

0.081 0.613

0.072 0.002 0.215*



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and good reading skills. Few of the children demonstrated substantial difficulty with the visual sequential reasoning or visual memory span tasks. It is not surprising that these children experienced much less difficulty with these tasks compared with the language or literacy tasks, but more surprising that the percentage of children scoring more than 1 SD below the mean was less than that based on normative data. The most likely explanation for this is sampling bias, as the group was self-selected. Consistent with previous research, we found auditory memory span (as a measure of auditory memory capacity) to be very strongly related to all outcomes, from phonological processing skills through to reading of single words. In particular, auditory memory span was a highly significant predictor of nonword repetition ability, accounting for 62% of the variance after taking account of the age at which the child was implanted. Poor performance on nonword repetition tasks is thought to reflect weak or underspecified phonological representations of words in the mental lexicon (Dillon & Pisoni 2006), which could occur as the result of the degraded auditory representation of speech provided by a cochlear implant. Nonword repetition deficits have been associated with poorer vocabulary knowledge and reading skills, and our results are consistent with this. The main purpose of this study was to explore the possibility that nonverbal visual cognitive processing factors may be useful in accounting for the variability in phonological processes, language and literacy abilities in children with cochlear implants. The measures of visual memory and reasoning ability were chosen based on a combination of theoretical and clinical rationale. In particular, the tests are clinically useful because they can be administered to very young deaf children who have not yet developed the spoken language skills needed to undertake the tests previously identified as associated with outcome (e.g., digit span, nonword repetition, or phonological processing). The results of this study suggest that these visual, nonverbal tests may indeed provide useful information for identifying children at risk of poor progress after cochlear implantation. The combination of visual memory span and visual sequential reasoning measures increased the amount of variation explained in the speech and language outcomes by around 20%, over that accounted for by age at implantation. For the majority of the outcome measures, visual memory span made the significant contribution to the variance accounted for by the regression models. It is interesting to note that the exception was the Phonological Processing subtest from the NESPY II where the visual sequential reasoning variable (the Fluid Reasoning composite from the Leiter-R) accounted for the significant proportion of variance. The NEPSY II Phonological Processing subtest may be considered to place greater processing demands on sequential processing skills, as the more difficult items in this test require the child to manipulate phonemes within words and produce them in the correct order. The relationship between visual memory span and outcomes is particularly interesting given that overall, as a group, these children with cochlear implants were performing well within the normal average range on the test of visual memory span, (only 7% of the sample scored 1 SD or more below the mean for the normalization sample). This suggests that clinically, if a child achieves a poor score on this test, further investigation of their information-processing abilities should be undertaken to assess specific areas of difficulty. In a clinical setting therefore, before the child has well-established spoken language capabilities,

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assessing his or her visual memory span and visual sequential reasoning abilities may provide useful information in deciding whether he or she is at risk of making poor progress in developing phonological processing skills, language and later on literacy skills. Similarly, when presented with a child who is making unexpectedly poor progress after implantation, and who may as yet be unable to tackle the more traditional, ­language-based assessments of specific learning difficulties, assessing these visual information-processing skills may be informative. If the child has some ability to produce spoken words, specifically the numbers one to nine, the results of this study suggest that administering a standardized test of auditory digit span such as that from the Children’s Memory Scale or Wechsler Intelligence Scale for Children IV, will provide further useful information. Clearly there are a number of other potential factors that contribute to the variance in outcomes, which would also need to be explored in a clinical assessment, such as the presence of a family history of dyslexia or specific language disorder, the degree of parental involvement in the child’s rehabilitation, any brain abnormalities evidenced on magnetic resonance imaging scans (for example after meningitis), or the child’s exposure to more than one spoken language in the home. All of these are likely to have an impact on progress in developing speech, language and literacy skills, but could not be quantified or accounted for in this study. Theoretically, as Pisoni et al. (2008, p. 61) note, the absence of auditory stimulation may disturb the development of neural systems and circuits other than those primarily involved in auditory processing (i.e., motor and visual systems), before implantation takes place. Delays in language acquisition during early development is likely to produce effects on processes not necessarily related to the early sensory processes of audition, for example, executive functions such as problem solving, attention and memory, particularly, memory for sequences and temporal order information. Therefore, in terms of our findings it is plausible that nonverbal, visual cognitive processes such as visual sequential memory, and visual sequential reasoning are affected by the early distortion or absence of auditory stimulation of the brain. As with much research in this area, one limitation of this study is the sample size, which while respectable in comparison with other published studies on pediatric cochlear implantation of this nature, is modest in view of the statistical analyses used. A second possible limitation is the range of measures used as either explanatory and outcome variables. In particular there are a relatively limited number of standardized visual tests available assessing reasoning or memory abilities, and even fewer that can be administered to young children. In contrast there are many potential tests of language and literacy and it was necessary to choose a selection that would hopefully cover a range of speech, phonological processing, language and literacy outcomes. In this study we examined the association between nonverbal cognitive abilities and outcomes in children aged between 5 and 12 years, some of whom had been using their cochlear implant for more than 8 years. Therefore for these children, valuable time has elapsed when specific information-processing deficits may have been identified and remedial intervention provided, for them to maximize the benefit to be derived from the implant(s). The advantage of the tests of visual sequential reasoning and memory used in this study is that they can be administered to deaf children as young as 2 years of age. For some children, this could be before they have actually received their cochlear implant(s). Therefore, for the first time, we have been

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able to identify potential early information-processing indicators of children at risk of difficulties in developing speech, language and literacy skills after cochlear implantation. However, it is recognized that observing an association between nonverbal cognitive abilities and outcomes at one time point postimplantation does not necessarily mean that these same cognitive abilities, if measured in younger deaf children, are predictive of future difficulties: this needs to be the focus of further research.

ACKNOWLEDGMENTS The authors declare no conflict of interest. Address for correspondence: Lindsey Edwards, Great Ormond Street Hospital for Children, Cochlear Implant Programme, Great Ormond Street, London WC1N 3JH, England, United Kingdom. E-mail: Lindsey. [email protected] Received September 13, 2012; accepted October 13, 2013.

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