A longitudinal investigation of morpho-syntax in children with Speech Sound Disorders

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Journal of Communication Disorders 43 (2010) 61–76

A longitudinal investigation of morpho-syntax in children with Speech Sound Disorders Jennifer Mortimer 1, Susan Rvachew *,1 School of Communication Sciences and Disorders, McGill University, Beatty Hall, 1266 Pine Avenue West, Montreal, Quebec, Canada, H3G 1A8 Received 8 December 2008; received in revised form 16 October 2009; accepted 24 October 2009

Abstract Purpose: The intent of this study was to examine the longitudinal morpho-syntactic progression of children with Speech Sound Disorders (SSD) grouped according to Mean Length of Utterance (MLU) scores. Methods: Thirty-seven children separated into four clusters were assessed in their pre-kindergarten and Grade 1 years. Cluster 1 were children with typical development; the other clusters were children with SSD. Cluster 2 had good pre-kindergarten MLU; Clusters 3 and 4 had low MLU scores in pre-kindergarten, and (respectively) good and poor MLU outcomes. Results: Children with SSD in pre-kindergarten had lower Developmental Sentence Scores (DSS) and made fewer attempts at finite embedded clauses than children with typical development. All children with SSD, especially Cluster 4, had difficulty with finite verb morphology. Conclusions: Children with SSD and typical MLU may be weak in some areas of syntax. Children with SSD who have low MLU scores and poor finite verb morphology skills in pre-kindergarten may be at risk for poor expressive language outcomes. However, these results need to be replicated with larger groups. Learning outcomes: The reader should (1) have a general understanding of findings from studies on morpho-syntax and SSD conducted over the last half century (2) be aware of some potential areas of morpho-syntactic weakness in young children with SSD who nonetheless have typical MLU, and (3) be aware of some potential longitudinal predictors of continued language difficulty in young children with SSD and poor MLU. # 2009 Elsevier Inc. All rights reserved.

1. Introduction Children with Speech Sound Disorders typically form the largest portion of a Speech–Language Pathologist’s caseload (American Speech-Language-Hearing Association, 2006). Some proportion of the Speech–Language Pathologist’s (SLP) caseload will have concomitant Speech Sound Disorder (SSD) and Specific Language Impairment (SLI). Shriberg, Tomblin, and McSweeney (1999) reported that 11–15% of children whose SSD persisted to age 6 years had concomitant SLI. In their population based study, 5–8% of children with persisting SLI also had SSD. ContiRamsden, Crutchley, and Botting (1997) found that 12% of a sample of 7-year-old children with language impairments could be characterized as having a phonological-expressive disorder in that they performed poorly on measures of * Corresponding author at: Beatty Hall, 1266 Pine Avenue West, Montreal, Quebec, Canada, H3G 1A8. Tel.: +1 514 398 4137; fax: +1 514 398 8123. E-mail addresses: [email protected] (J. Mortimer), [email protected] (S. Rvachew). 1 Tel.: +1 514 398 4137; fax: +1 514 398 8123. 0021-9924/$ – see front matter # 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.jcomdis.2009.10.001

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articulation accuracy and expressive syntax. Although the proportion of children who have comorbid difficulties in these areas is small, appropriate identification of this subgroup of children with SSD may be clinically important. Children who present with delays in both areas may be at higher risk for other comorbid development disorders such as attention deficit disorder (McGrath et al., 2008). In general, children with comorbid SSD and SLI appear to be at greater risk for poor academic outcomes than children with SSD alone (Lewis, Freebairn, & Taylor, 2000; Young et al., 2002). Identification of this subgroup may allow for more appropriate clinical management of these children as well as appropriate targeting of scarce clinical resources among caseloads of children with SSD. The identification of expressive language problems in young children with moderate and severe SSD presents a clinical challenge. When speech accuracy and intelligibility are very poor, valid scoring of expressive language tests may be impossible with the differentiation of speech sound versus morphological errors being especially difficult. Research on the longitudinal development of language skills in children with SSD may help us to illuminate markers that serve to identify children whose language difficulties persist even as their articulation accuracy improves. The current study was conducted with the goals of providing much-needed data on the patterns of morpho-syntactic development of an understudied population, and obtaining potentially useful insight into the language profiles of young children with delayed speech development. 1.1. Morphological development in children with SSD In recent years, two aspects of morpho-syntactic development in English have achieved a certain prominence in studies of developmental language disorders: the first being the production of finite verb morphology (e.g., third person singular -s, past tense -ed, and auxiliary and copular ‘‘be’’), and the second, the use of embedded clausal structures (e.g., ‘‘I think she’s happy’’, ‘‘I don’t know what happened’’). In particular, finite verb morphology has attracted interest as a potential clinical marker for SLI in English (Rice & Wexler, 1996), therefore, the examination of verb morphology production in other populations at risk for language difficulties is warranted. In addition, an appreciation of recursive grammar is considered by some researchers to be central to language acquisition (Hauser, Chomsky, & Fitch, 2002), and the question of how this capacity develops, and its relation to other components of language acquisition (such as vocabulary development) is the focus of much debate. Embedded clause use is a form of recursive grammar, and is often considered in studies of language development disorders (see Owen & Leonard, 2006). Both finite verb morphology and embedded clause production are examined in the current study. A central consideration in studies of verb morphology production in children with SSD is determining whether or not dropped inflections can be explained as a product of the articulation deficit. Comparing the expressive language of two groups of articulation-disordered children2 – syllable reducers, who tended to omit phonemes, and substituters, who tended to make substitution errors – Smit and Bernthal (1983) found that only the syllable reducers were more likely than typically developing (TD) comparison children to omit free and bound functors, as indexed by the Carrow Elicited Language Inventory (CELI—Carrow, 1974; as referenced in Smit and Bernthal). Substituters were more likely than TD children to make substitution errors on functors, but not on other word categories. These data are difficult to interpret. At first glance they suggest that the type of morpho-syntactic problems evinced by these children is specific to their articulation disorder. However, the categories of ‘‘free’’ and ‘‘bound’’ functors on which the children were tested were rather broad, and encompassed ‘‘copulas, auxiliaries, modals, the infinitive particle to, articles, prepositions, negatives and conjunctions’’ (Smit & Bernthal, 1983, p. 126) for the first category, and inflectional endings for the second. Relationships between articulation skills and errors on specific types of inflectional affixes were examined more closely by Rvachew, Gaines, Cloutier, and Blanchet (2005) in a group of children with SSD. The inflectional affixes of interest were the plural (-s), possessive (-’s), and regular present-tense third person singular morphemes (-s), and their production was compared to that of word-initial and word-final /s/ and /z/, singly and in clusters, in monomorphemic words. Results showed that the children had problems with inflection production that exceeded their difficulties with word-final singleton and cluster /s/ and /z/. Discrepancies were particularly apparent with respect to the regular present-tense third person singular morpheme. This indication of a potential weakness among children with SSD in finite verb morphology was supported by a study by Haskill and Tyler (2007). Finite verb morphology (third person singular -s, past tense -ed, and auxiliary and

2

In the review of previous studies on language and Speech Sound Disorders, the original diagnostic labels for children in the experimental groups are retained for purposes of clarity.

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copular ‘‘be’’) was shown to be poor in a group of children with Speech (Phonological)-Language Impairment (PLI) when compared to a group of children with Language-Only Impairment (LI). Both groups had depressed expressive language scores, but significant difficulties with finite verb morphology relative to a typically developing control group were observed only in the groups with PLI. Even the subgroup of PLI children who did not show any particular tendency to omit final consonants or reduce final clusters omitted the third person singular morpheme more frequently than children in the LI or control groups. Less information is available on finite verb morphology production by children in this population compared to their general syntactic skills. Paul and Shriberg (1982) found that about half of a sample of 30 children with speech delay showed difficulty with plural, possessive, regular past tense, and regular third person singular inflectional affixes in relation to their degree of expressive syntactic development. These morphemes were chosen for analysis due to potential interactions with phonological processes, however, and not to examine finite verb inflections specifically. Rvachew et al. (2005) found that third person singular -s production correlated well with Mean Length of Utterance in Words in their group of children with Speech Delay. Nevertheless, the question of how well children with SSD perform on finite verb morphology production relative to Mean Length of Utterance (MLU) when matched to children with TD has never been directly addressed. 1.2. Syntactic development in children with SSD Children diagnosed with SSD show a general tendency of reduced language production when measured by various measures of utterance complexity, including MLU. Davis (1937) found a reduced number of words per sentence and fewer subordinate clauses in a group of children with articulation difficulties compared to TD children. In a study of children who displayed ‘‘infantile speech’’ with articulation errors, Menyuk (1964) observed that they produced fewer syntactic transformations (among them infinitival complements, participial complements, relative clauses, etc.) when compared to children with typical development. Shriner, Holloway, and Daniloff (1969) found that children with articulation problems had a lower mean number of words per sentence unit than children with typical language, and less developed syntax according to a classification scheme of noun and verb phrases. In many early studies, sentence ‘‘complexity’’ was indexed by a composite measure that included, among other variables, embedded clause use. Correlations were found between speech sound production and length of utterance unit as well as a sentence complexity composite in a sample of typically developing children investigated by Williams (1937). Children with defective articulation investigated by Vandermark and Mann (1965) produced language samples that elicited a lower structural complexity composite score than those of children with TD. A study by Templin (1957) provided cross-sectional data on correlations between articulation scores and productive language in a cohort of 480 children ranging from age 3 to 8 years. Analyses of the children’s language output included a measure of remark length and a composite score of complexity of remark. High correlations were seen among articulation and language variables in the younger children, but size of correlation tended to decline as the groups increased in age (the author suggested that ceiling effects among the older children could be a reason for the lower correlations). Findings contrary to the general trend of impaired language in children with articulation problems were obtained by Yedinack (1949), however. In this study, no significant differences were found between children with articulation disabilities and TD children when oral language was evaluated for length of utterance and grammatical complexity using a composite score. Similarly, Winitz (1959) noted no significant correlations between articulation score and length of utterance or a composite structural complexity score in a group of children sampled randomly from a kindergarten population. One difficulty in interpreting these results is caused by the widespread use of an omnibus syntactic complexity score. Williams (1937), for example, assigned different weights to unintelligible, simple, complex, and compoundcomplex utterances to derive an overall score. Thus, compound clausal constructions as well as embedded clause use were incorporated into the score. Yedinack (1949) used a score that assigned compound constructions less weight than embedded constructions. The current study will examine embedded constructions in isolation. Although there is evidence that children with SSD have reduced linguistic output as indexed by MLU, and produce fewer complex syntactic structures in the form of embedded clauses relative to TD children, there is a question as to whether proportion of embedded clausal structures produced is commensurate with MLU, a point which will be investigated in this work.

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1.3. Longitudinal morpho-syntactic development Data on longitudinal relationships between articulation and morpho-syntax in children with SSD are scarce. Due to the lack of research, early markers that could potentially identify later morpho-syntactic outcomes in children with SSD are poorly understood. Mortimer and Rvachew (2006) found that subject case-marking on pronouns in pre-kindergarten predicted unique variance in finite verb morphology a year later in a sample of children with SSD. Amorosa, von Benda, and Wagner (1990) provide very interesting German-language data on morpho-syntax in children with articulation difficulties: the study showed links between each of non-verbal cognition, grammar comprehension, visual sequential memory, and grammar output a year later in children with speech and language disability. Phonological working memory was assessed in their study, but performance was too low to serve as a predictor of language skills. 1.4. Overview of the current study In the current study, expressive language development was examined longitudinally. The children’s performance on measures of speech accuracy, phonological processing, and expressive language are described at two time points: first, during the spring of the children’s pre-kindergarten year, and second, during the spring of the children’s Grade 1 year. Performance on these measures is described for four clusters of children defined in terms of patterns of MLU at these two times. MLU is a commonly reported measure of general expressive language development in children. In a recent study, Rice, Redmond, and Hoffman (2006) examined the longitudinal stability of MLU scores in a group of children with Specific Language Impairment (SLI) and in a group of younger TD children. Starting at age 5 for the children with SLI, and at age 3 for the children with TD who had comparable MLU, it was found that both groups showed similar growth in MLU over a 5-year period. These results support the practice, in research on language development disorders, of using MLU scores as a longitudinal index of general expressive language development, as MLU growth curves remained stable even among children with language impairment. When examining MLU at the pre-kindergarten and Grade 1 time points in the current study, four clusters of children emerged: Clusters 1 and 2 had relatively good MLU in pre-kindergarten and good MLU outcomes 2 years later; Clusters 3 and 4 had low MLU scores in pre-kindergarten but only Cluster 4 showed a persistent lag in MLU throughout the time course of the study. Children in Cluster 1 showed normally developing speech throughout the study while children in the remaining clusters were receiving intervention for SSD at the time of intake into the study. To summarize, the four clusters were: Cluster 1, Typical Speech–Language; Cluster 2, SSD – High MLU; Cluster 3, SSD – Improving MLU; Cluster 4, SSD – Low MLU. Comparisons were made among groups on a variety of language measures. This design allowed the following research questions to be addressed: (1) Are there aspects of expressive language ability that are reliably associated with SSD, even when the children demonstrate generally normal expressive language skills (as indexed by MLU) and normal receptive vocabulary skills? This question was examined by a comparison of Cluster 1 to Cluster 2. (2) Are there aspects of expressive language ability that serve to predict growth in expressive language skills among children with SSD? This second question was investigated by comparing the scores from Clusters 3 and 4 on dependent measures. 2. Methods 2.1. Participants This study analyzed data from a larger project on phonological awareness skills in a group of children with SSD (Rvachew, 2006; Rvachew, 2007; Rvachew & Grawburg, 2006; Rvachew & Grawburg, 2008). These children were referred to the project when they were 4- and 5-year olds receiving or waiting to receive speech therapy for remediation of a Speech Sound Disorder.3 Speech pathologists identified these children on the basis of a score below the 16th percentile on a standardized measure of articulation abilities. Additionally, the children (a) had received a primary diagnosis of speech delay (although language impairment and suspected childhood apraxia of speech were not

3 Although these children were recruited from the active treatment caseloads or treatment waitlists of speech therapy departments at two major children’s hospitals, we have no information about the intensity, duration, or focus of the children’s treatment program and thus no inferences about the impact of their treatment experience on their test performance in this study can be made.

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exclusionary criteria); (b) had hearing and oral-motor function within normal limits as assessed by the child’s clinician; (c) had English as a primary language; (d) did not have a Speech Sound Disorder that was secondary to other conditions such as sensory-neural hearing loss, Down syndrome, cerebral palsy, or cleft palate. The children in the typically developing comparison group were matched to the children with SSD on age and socio-economic status according to a Blishen score derived from a combination of the parents’ occupation and education levels (Blishen, Carroll, & Moore, 1987). The resulting Blishen scores ranged from 31 (high school not completed) to 101 (professional credentials), with a mean of 59 (some post-secondary education). The children with typical development were recruited from day care and preschool programmes. English was the primary language, and parent and teacher report indicated these children to be healthy with typical development. The pre-existing data set from the longitudinal study on phonological awareness was analyzed to determine whether patterns in the language development of these children could be discerned. Four clusters emerged from the data set, comprising 37 children in total. Cluster 1 (Typical Speech–Language) consisted of 11 children (7 girls) who scored within the average range on tests of articulation accuracy and receptive language and achieved MLUs of 5.36 and 7.77 at prekindergarten and first grade, respectively. The remaining consisted of the children who scored below on normal limits on a standardized measure of articulation accuracy and within normal limits on a standardized measure of receptive vocabulary. These children were grouped according to their MLU performance in pre-kindergarten and Grade 1. Cluster 2 (SSD – Stable High MLU) had 10 children (5 girls) with MLU in pre-kindergarten and Grade 1 statistically comparable to that of the typically developing group. Cluster 3 (SSD – Improving MLU) had 11 children (5 girls) with significantly lower pre-kindergarten MLU than Cluster 1 but Grade 1 outcomes consistent with that of the typically developing group. The 3 boys and 2 girls in Cluster 4 (SSD – Stable Low MLU) demonstrated significantly poorer MLUs relative to the typically developing children at pre-kindergarten and first grade. Differences among the clusters on the MLU (and other) variables were evaluated using bootstrap t-tests. Cluster characteristics at pre-kindergarten and Grade 1 assessment times are presented in Tables 1 and 2. A detailed description of the nature of the speech errors produced by the children in the larger study sample from which these children were drawn is provided in Rvachew, Chiang, and Evans (2007). 2.2. Procedures Assessors in this study were Speech-Language Pathologists hired on contract or graduate students in SpeechLanguage Pathologists under the supervision of speech language pathologists with certification from the Canadian Association of Speech–Language Pathologists and Audiologists. The children were evaluated in one 75-min session, or (in a few cases), two 40-min sessions. The tasks administered to the children included indices of receptive vocabulary and articulation. Speech samples were also obtained through a task in which the child was asked to describe a picture book to the assessor (Good dog, Carl; Day, 1986). These samples were transcribed according to Systematic Analysis of Language Transcripts conventions (SALT; Miller & Chapman, 2005) and analyzed according to the protocols discussed below. In addition, a phonetic transcription of the samples was used to find the Percentage of Consonants Correct (Shriberg & Kwiatkowski, 1982). Ten language samples were chosen at random and reanalyzed by an independent coder to ascertain inter-rater reliability for PCC, MLU, and morpho-syntactic analyses (finite verb morphology composite; Development Sentence Score, Lee, 1974; and Complex Sentence Score), with the intraclass correlations reported for the 10 pairs of sample-level statistics for each of these measures below. Receptive vocabulary. The Peabody Picture Vocabulary Test-Third Edition (PPVT; Dunn & Dunn, 1997) was used to assess receptive vocabulary. The PPVT provided another measure of general language development as defined by Rice et al. (2006) that, like MLU, shows a stable and predictable growth trajectory with age. Articulation. The Goldman–Fristoe Test of Articulation-Second Edition (GFTA; Goldman & Fristoe, 2000) is a picture-naming task serving as a measure of articulation skills. PCC was calculated from narrow phonetic transcriptions of free speech samples, recorded while the child was talking about a wordless picture book. (Omissions, substitutions, and distortions of consonants including rhotics were counted as errors.) The intraclass correlation for the PCCs determined independently by two coders yielded a reliability of 0.95. Mean Length of Utterance in Morphemes. MLU scores were based on the pre-kindergarten and Grade 1 language samples for each child. Calculations for MLU scores were performed by SALT-Standard Version 8 (Miller & Chapman, 2005). The intraclass correlation for the MLUs determined independently by two coders yielded a reliability of 0.99. Finite verb morphology composite. This composite is calculated according to the combined percentage of correctly produced auxiliary and copular ‘‘be’’, present third person singular -s, and past tense -ed morphemes in

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Table 1 Pre-kindergarten descriptive statistics for comparison and experimental children. Group 1: Typical Dev.

Group 2: SSD

Group 3: SSD

Group 4: SSD

Age in months Mean SD Range

59.09 3.36 54.0–65.0

57.30 3.77 53.0–66.0

56.64 1.91 54.0–59.0

60.00 3.81 54.0–64.0

SES Mean SD Range

58.55 8.23 55.0–76.0

47.50 7.17 35.0–55.0

61.23 22.18 31.0–101.0

58.00 14.32 41.0–73.0

MLU in morphemes Mean SD Range

5.36 0.82 4.13–6.86

5.68 1.12 4.31–7.69

3.20 0.51 2.34–4.03

2.80 0.75 1.77–3.73

GFTA-2%ile Mean SD Range

51.73 20.44 21.0–85.0

6.45 3.98 0.50–14.00

4.77 3.98 0.50–13.0

3.30 2.99 0.50–7.0

PCC Mean SD Range

85.41 7.84 75.17–97.0

69.26 11.59 51.79–91.64

59.36 6.99 50.21–75.11

58.43 12.98 44.29–71.77

PPVT standard scores Mean SD Range

108.09 9.99 90.0–119.0

No. of utterances per sample Mean 61.23 SD 20.92 Range 36.0–103.0

105.50 8.15 94.0–123.0

107.81 14.56 92.0–138.0

108.20 4.21 104.0–115.0

45.30 11.25 35.0–71.0

69.18 12.92 56.0–106.0

68.80 23.34 47.0–106.0

Typical Dev. = typical development; SSD = Speech Sound Disorders; MLU in morphemes = Mean Length of Utterance in Morphemes; SES = socioeconomic status; GFTA-2%ile = Goldman–Fristoe Test of Articulation-Second Edition percentiles (Goldman & Fristoe, 2000); PCC = Percentage Consonants Correct; PPVT-III = Peabody Picture Vocabulary Test-III (Dunn & Dunn, 1997).

obligatory contexts in a speech sample (see Bedore & Leonard, 1998; Goffman & Leonard, 2000). Among English-language speakers with SLI, the production of finite verb morphemes has been found to be impaired relative to MLU-matched children (Rice & Wexler, 1996). This composite in particular has been found to be a useful tool in identifying individuals with SLI (Bedore & Leonard, 1998). The intraclass correlation for the reliability analyses was 0.99. Development Sentence Score. Lee (1974) based this measure of development on the order of appearance of certain morpho-syntactic constructs in the speech of typically developing children. The categories of syntactic forms assessed are indefinite pronouns or noun modifiers, personal pronouns, main verbs, secondary verbs, negatives, conjunctions, interrogative reversals, and wh-questions. Within each category, later-appearing, more sophisticated syntactic forms are given more weight when scoring than are earlier-appearing forms. Because some of our language samples contained fewer than the 50 utterances required for Developmental Sentence Score (DSS) analysis, a modified protocol was used for all language samples to obtain a DSS. The five sentences with the highest DSS from each language sample were identified and their mean calculated. (See Devescovi, Caselli, Marchione, Reilly, & Bates, 2003, for a similar strategy used in calculating grammar scores.) Reliability analyses yielded an intraclass correlation of 0.96. Complex Sentence Score. Embedded clauses in language output are an example of recursion. The specificity of the capacity of recursion to language and to human cognition is hotly debated (Hauser et al., 2002; see reply by Pinker & Jackendoff, 2005; and subsequent reply by Fitch, Hauser, & Chomsky, 2005). In the current paper embedded

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Table 2 Grade 1 descriptive statistics for comparison and experimental children. Group 1: Typical Dev.

Group 2: SSD

Group 3: SSD

Group 4: SSD

83.18 3.84 75.00–87.00

82.30 3.43 78.00–90.00

81.45 2.07 79.00–85.00

85.20 2.39 82.00–88.00

7.77 1.28 6.15–10.44

9.18 2.23 6.25–12.62

7.49 1.28 5.97–10.00

5.00 1.09 2.95–5.84

GFTA-2%ile Mean SD Range

39.72 20.51 11.00–62.00

16.45 16.19 0.50–55.00

24.55 17.74 11.00–62.00

8.10 5.25 0.50–13.00

PCC Mean SD Range

88.96 8.04 72.56–99.00

88.86 7.23 74.39–98.21

89.20 3.62 83.79–94.87

81.59 18.32 53.13–98.23

Age in months Mean SD Range MLU in morphemes Mean SD Range

PPVT standard scores Mean SD Range

105.91 10.98 90.0–125.0

No. of utterances per sample Mean 42.18 SD 15.34 Range 26.0–82.0

106.60 8.24 96.0–122.0

107.64 12.09 93.0–129.0

101.80 10.76 94.0–120.0

48.10 10.29 33.0–69.0

46.09 11.00 28.0–63.0

60.20 14.94 44.0–82.0

Typical Dev. = typical development; SSD = Speech Sound Disorders; MLU in morphemes = Mean Length of Utterance in Morphemes; GFTA2%ile = Goldman–Fristoe Test of Articulation-Second Edition percentiles; PCC = Percentage Consonants Correct; PPVT-III = Peabody Picture Vocabulary Test-III (Dunn & Dunn, 1997).

constructions were identified following Thordardottir, Chapman, and Wagner (2002) who in turn used a classification system developed by Paul (1981). Nine embedded clausal types are listed: (a) (b) (c) (d) (e) (f) (g) (h) (i)

Simple infinitive clauses with equivalent subjects (‘‘Then he/’s try/ing to get the food’’). Full propositional complements (‘‘I think . . . the dog open/ed all of them maybe’’). Simple non-infinitive wh-clauses (‘‘I don’t know what he/’s draw/ing over there’’). Infinitive clauses with different subjects (‘‘he does/n’t want him to touch anything’’). Utterances with relative clauses (‘‘I saw a man whose name is Carl’’). Utterances with gerund and/or participle clauses4 (‘‘And then mommy come there looking for baby’’). Unmarked infinitive clauses (‘‘And he and the little baby let him eat some sausage’’). wh-Infinitive clauses (‘‘Because they don’t know how to feed babies’’). Quotes as full clauses (‘‘And then she said ‘‘you’re a good dog’’).

Each example of an embedded clause in a language sample was awarded one point, with the total number of points then being calculated and divided by the number of different utterances in the sample to form a Complex Sentence Score. Attempts at embedded clauses were given full points, even if they contained grammatical errors, such as the omission of finite verb morphemes. The Complex Sentence Score category was further divided into two types of clauses: finite embedded clauses and non-finite embedded clauses. The intraclass correlation for a subset of language samples analyzed by independent coders on the Complex Sentence Score measure was 0.94.

4

In the original references this category was labelled ‘‘Gerund Clauses’’ only.

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Finite embedded clauses. Full propositional complements, simple non-infinitive wh-clauses, utterances with relative clauses, and quotes as full clauses were all considered examples of finite embedded clauses, since they contained finite markings on an embedded verb. A distinction was made between finite and non-finite embedded clauses for experimental purposes in the event that finiteness in embedded clauses might prove to be particularly difficult for this population of children, who have already been shown to have difficulty with finite verb morphology (Haskill & Tyler, 2007; Rvachew et al., 2005). Non-finite embedded clauses. Simple infinitive clauses with equivalent subjects, infinitive clauses with different subjects, utterances with gerund and/or participle clauses, unmarked infinitive clauses, and wh-infinitive clauses were classified as non-finite embedded clauses. 3. Results Since sample sizes were small and unequal, and since homogeneity of variance could not be assumed, nonparametric methods (specifically, a series of bootstrap t-tests) were used for between-group comparisons. In the Statistical Analysis Software (SAS) procedures used in this study, bootstrapping a comparison of means involves pooling the sample residuals, then resampling with replacement from the pool to produce a bootstrap sample. p-Values are calculated, and the data are sampled again. In the study, the number of iterations was set at 100,000. The adjusted pvalue for a given test is derived from a comparison of the p-values from the samples (Westfall, Tobias, Rom, Wolfinger, & Hochberg, 1999). This method of bootstrap hypothesis testing has the advantage that it makes no assumptions about the normality of the underlying distribution of the data (Westfall et al., 1999), or the equality of the variances (Efron & Tibshirani, 1993). A second issue in analyzing the data was the large number of between-group comparisons that needed to be run. As this was an exploratory study, it was decided to set liberal alpha-levels of 0.05 without making the Bonferroni adjustment for multiple comparisons, following the rationale set by Shriberg et al. (2000). Lahey and Edwards (1995) argue for reporting high alpha levels (0.10) when the purpose of a study is to ‘‘generate rather than to test hypotheses.’’ In the present case, it was felt that the risk of making a Type I error was secondary to potentially missing a noteworthy characteristic of language development among children with SSD that could be tested in future research (a Type II error). The details of the statistical analyses are provided in Table 3 and illustrated in Fig. 1(parts A–F). These results will be discussed in relation to the primary research questions in order as follows: (1) Are there aspects of expressive language ability that are reliably associated with SSD? This analysis will focus on a comparison of Cluster 1 (Typical Speech–Language) with the remaining clusters, especially Cluster 2 (SSD – Stable High MLU); (2) Are there aspects Table 3 p-Values for Bootstrap comparisons between groups on morpho-syntactic variables. Group comparisons

FVM pre-k

FVM Grade 1

DSS pre-k

DSS Grade 1

MLU pre-k

MLU Grade 1

1 1 1 2 2 3

<0.0001 <0.0001 <0.0001 0.5601 0.2650 0.0443

0.3972 0.4162 0.0288 0.9003 0.1147 0.0727

0.0269 0.0088 0.0110 0.4672 0.0353 0.0954

0.6681 0.8959 0.0625 0.6767 0.0144 0.0051

0.3258 <0.0001 <0.0001 <0.0001 0.0002 0.2879

0.0736 0.8101 0.0006 0.0642 0.0017 0.0024

and and and and and and

2 3 4 3 4 4

Group comparisons

Finite embedded clause pre-k

Finite embedded clause Grade 1

Non-finite embedded clause pre-k

Non-finite embedded clause Grade 1

Complex embedded clause pre-k

Complex embedded clause Grade 1

1 1 1 2 2 3

0.0403 0.0668 0.0488 0.7258 0.3408 0.2827

0.2661 0.5828 0.5674 0.7572 0.1844 0.3980

0.7028 0.0548 0.1219 0.0111 0.0222 0.5801

0.7321 0.1869 0.0615 0.1869 0.0084 0.1762

0.0999 0.0206 0.0365 0.2045 0.0359 0.1528

0.5061 0.1353 0.1330 0.2356 0.0926 0.6180

and and and and and and

2 3 4 3 4 4

FVM = finite verb morphology; DSS = Developmental Sentence Score (Lee, 1974); MLU = Mean Length of Utterance; pre-k = pre-kindergarten.

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Fig. 1. Mean scores by group and assessment time on the: (A) Mean Length of Utterance variable; (B) finite verb morphology variable; (C) Developmental Sentence Score variable; (C) finite embedded clause variable; (E) non-finite embedded clause variable; (F) Complex Sentence Score variable.

of expressive language ability that serve to predict growth in expressive language skills among children with SSD? The second question will focus on a comparison of Cluster 3 (SSD – Improving MLU) and Cluster 4 (SSD – Low MLU). 3.1. Effect of SSD on language production Examination of the between-group comparisons on language output, as shown in Table 3, indicated weak performance on some variables in pre-kindergarten among the children with SSD, even for the group matched on MLU (Cluster 2) to the children with Typical Speech–Language (Cluster 1). Fig. 1A illustrates performance on the group selection variable, MLU, showing MLU similar for Clusters 1 and 2 at pre-kindergarten and significantly delayed for Clusters 3 and 4 at pre-kindergarten and a persistent delay for Cluster 4 at Grade 1. In pre-kindergarten, mean finite verb morphology scores were low for all the groups of children with SSD, however (see Fig. 1B). DSS were also significantly depressed among the children with SSD during pre-kindergarten (see Fig. 1C). Contrasts show that

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children with SSD had finite embedded clause scores that were marginally weaker relative to the children in Cluster 1; however, problems in this area appeared to have resolved by Grade 1 (see Fig. 1D). Children with SSD did not perform significantly differently from the Typical Speech–Language Cluster on the non-finite embedded clause measure or on the omnibus Complex Sentence Score in pre-k or Grade 1, with Clusters 1 and 2 demonstrating similar levels of use for these language structures (see Fig. 1E and F). In summary, a comparison of Cluster 1 and 2 indicates that children with SSD have significantly poorer finite verb morphology than do children with Typical Speech–Language development, even when their MLU is within the normal range. 3.2. Effect of MLU on language production Clusters 3 and 4 had very low MLU in pre-kindergarten compared to Clusters 1 and 2, who had age-appropriate MLU throughout the study (see Fig. 1A). However, Cluster 3 achieved age-appropriate MLU by the end of first grade whereas Cluster 4 continued to lag behind the other clusters on this measure. Cluster 4 also presented with poorer finite verb morphology and DSS performance relative to Cluster 3 at pre-kindergarten with marginal differences between these clusters still apparent in first grade. Although Fig. 1D and E are suggestive of difficulties with complex sentence use by Cluster 4, none of the apparent differences relative to Cluster 3 were statistically significant at pre-kindergarten or first grade and thus the use of finite and non-finite embedded clauses does not appear to be a reliable predictor of language outcomes for these children. In summary, while all children with SSD showed significant difficulties with morpho-syntax, those children who demonstrated persistent expressive language delays showed the most severe delays in this aspect of language development as preschoolers in this study. 4. Discussion The current study examined longitudinal language data from children with Typical Speech–Language development and children with SSD who were grouped according to Mean Length of Utterance Score in prekindergarten and in Grade 1. The language variables marked for particular attention were the embedded clause production variables and the finite verb morphology composite. Proportion of embedded clause production was assessed in order to answer longstanding questions as to whether syntactic development might be found to be impaired in children with SSD who nevertheless display typical language output as measured by Mean Length of Utterance. Comparisons at pre-kindergarten between the children with Typical Speech–Language (Cluster 1) and children with SSD matched on MLU (Cluster 2) indicate that children with SSD may indeed experience difficulties with complex syntax. With regards to finite verb morphology, the production of these morphemes has been shown to be inconsistent in children with SSD in a manner that cannot be explained as the by-product of a deficit in articulatory output: finite verb morphology is specifically problematic for these children (Haskill & Tyler, 2007; Rvachew et al., 2005). Given the research supporting finite verb morphology as a possible diagnostic tool for children with language impairment (Rice & Wexler, 1996), close attention was paid in the current study as to whether children with SSD with Low MLU (Cluster 4) had difficulties with finite verb morphology relative to the other children with SSD. 4.1. Expressive language skills associated with SSD The first research question motivated a comparison of expressive language outcomes for Cluster 1, a typically developing group, and Cluster 2, a group of children with SSD but matched on age, MLU, and receptive vocabulary score to children with typical development. The intent of this comparison was to determine whether expressive language traits specific to children with SSD could be found even when these children produced typical output as measured by MLU and good receptive vocabulary. Results at pre-kindergarten age showed low performance on DSS and finite embedded clause production by children with SSD during the pre-kindergarten assessment. Productive syntax was therefore poor in children with SSD despite an age appropriate trajectory of general expressive language development as indexed by MLU. That surface articulation errors could explain in part low DSS is a possibility, since some DSS points are specifically awarded for morphemes (such as finite verb morphemes), that happen to be characterized by high articulation demands, as evidenced by the pervasiveness of /s/ errors among children with articulation disorder (Dodd, Holm, Crosbie, & McCormack, 2005). The DSS examines eight different grammatical

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categories (ranging from indefinite pronouns to wh-questions) at different stages of development, and several other categories (for example, interrogative reversals), are also dependent on verb morphology production. A richer source of information perhaps is the finite embedded clause results. Children in this study were given full points even for attempts at finite embedded clauses, such that superficial difficulties with the articulation of alveolar stops or fricatives should not have depressed scores in the children with SSD. Nevertheless, Cluster 2 still showed poor performance on this variable, although they performed similarly on non-finite embedded constructions to children with Typical Speech–Language (Cluster 1). The reason for this finding is unclear: it is known that some non-finite embedded constructions (such as non-finite complement clauses) appear developmentally before some finite embedded constructions (such as finite complement clauses) in the speech of typically developing children (Diessel, 2004). Thus, syntax in the children with SSD may simply have been late to develop. However, our categories of finite vs. non-finite embedded clauses were each quite broad, and both covered a range of early and late-appearing types of embedded clauses. Nevertheless, it was observed that Cluster 2 children had caught up to their typical-language peers in finite embedded clause production by Grade 1 testing time. With regards to the finite verb morphology results, Cluster 2 children also produced significantly poorer finite verb morphology composite scores than Cluster 1 during the pre-kindergarten assessment. As stated earlier, this finding is consistent with prior research (Haskill & Tyler, 2007; Rvachew et al., 2005); however, neither this study nor the two previous studies provide much insight into the cause of this behavioural pattern. Cluster 2 achieved finite verb morphology composite scores that were equivalent to the typically developing Cluster 1 by Grade 1, however. 4.2. Traits in pre-kindergarten signalling continued language delay Cluster 3 and Cluster 4 demonstrated significantly shorter MLUs than their typically developing peers during the pre-kindergarten assessment, but Cluster 3 achieved an age-appropriate MLU by Grade 1, in contrast to Cluster 4, a small group of children whose expressive language deficit persisted throughout the 2-year period of the study. Pre-kindergarten speech samples were examined for any variables that might be associated with this difference in MLU outcome in order to address the second research question. With respect to syntactic variables, these two clusters did not differ from each other on the use of finite and non-finite embedded complex clauses. Performance on the DSS was low for Cluster 4 relative to the other clusters at pre-k, although comparisons with Cluster 3 did not reach significance. Cluster 4 (SSD – Low MLU) also had weak finite verb morphology skills at pre-kindergarten compared to Cluster 3 (SSD – Improving MLU). This was in fact the only variable that appeared to differentiate at pre-kindergarten between Clusters 3 and 4. Low finite verb morphology score would therefore seem to predict poor MLU, which would be consistent with findings by numerous researchers showing finite verb morphology production to be exceptionally difficult for individuals with language impairment (Leonard, Camarata, Pawłowska, Brown, & Camarata, 2006; Rice & Wexler, 1996). However, finite verb morphology score was not particularly depressed in Cluster 4 relative to Cluster 2 (SSD – High MLU). Thus, poor finite verb morphology among the children with SSD did not inevitably predict Low MLU outcomes. It may be that a combination of depressed MLU and finite verb morphology scores is required to identify children with SSD who are at risk of delayed language outcomes. An issue that arises in interpreting the data is the question of whether some groups with SSD may have had a greater tendency to drop word-final consonants than did other groups. Studies by Rvachew et al. (2005) and Haskill and Tyler (2007) address this point. In a group of children with SSD Rvachew et al. (2005) found difficulties with inflections (and particularly with regular present-tense third person singular morpheme) beyond those problems with non-inflectional word-final /s/ and /z/. Haskill and Tyler (2007) showed that children with Phonological-Language Impairment with and without a propensity to word-final consonant deletion had lower finite verb morphology scores than did typically developing children or children with LI alone. The current study’s results may be useful in that they show that poor finite verb morphology combined with low MLU in pre-kindergarten is associated with limited language output 2 years later. One motivation for recent research into finite verb morphology in children with SSD has been to view performance in this area in a population traditionally closely associated with SLI (Haskill & Tyler, 2007; Rvachew et al., 2005). Currently, the nature of the relationship between SSD and SLI is poorly understood. Several older studies report that a high percentage of children diagnosed with SSD also have language impairment. A frequently

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cited figure is 40–60% (Haskill & Tyler, 2007, referencing Shriberg and Austin, 1998; and Shriberg & Kwiatkowski, 1994). Haskill and Tyler emphasize research indicating a high co-morbidity of SLI when discussing morphology results of an investigation of children with speech–language impairment. However, the criteria for diagnosis of language impairment in some of studies showing extensive overlap are not always clear (as in Shriberg & Kwiatkowski, 1994; Shriberg, Kwiatkowski, Best, Hengst, & Terselic-Weber, 1986), and are not consistent with more recent SLI identification methods. Other factors influencing results may be the age at which the children with SSD are assessed (Lewis et al., 2006b) and the size and nature of the population sample (Shriberg et al., 1999). In an extensive epidemiological survey, Shriberg et al. (1999) found low comorbidity rates of SLI (11–15%) among 6year-old children with SSD. The degree of overlap between SLI and SSD is an important consideration, because it raises questions about the specificity of finite verb morphology as a diagnostic marker for SLI. If it is true that children with SSD and SLI belong to genetically distinct populations, and that both groups tend to show difficulty with finite verb morphology, then such a finding would call into question any hypothesis that a developmental finite verb morphology deficit in English is a unique manifestation of the genetic profile associated with SLI. In fact, research on children with Down syndrome indicates that this population, also characterized by productive language delay, has particular difficulty with some aspects of finite verb morphology (Eadie, Fey, Douglas, & Parsons, 2002; Laws & Bishop, 2003). Roberts, Rice, and Tager-Flusberg (2004) and Tager-Flusberg (2006) describe a subtype of children with autism (children with autism and language impairment) who also show weakness in this area. Other explanations must be considered for the apparent fragility of finite verb morphemes in the productive speech of English-speaking children who, for different reasons, may have delayed language. This aspect of English-language processing might be viewed as a construction whose expression is influenced by a multiplicity of factors, some of which may be commonly affected among children with language impairments whose language difficulties stem from a broad variety of etiological backgrounds. Recent work by Mortimer (2007), using structural equation modeling, showed good fit for a model in which prekindergarten articulation skills in children with SSD predicted morphology skills a years later. In studies of child language development disorders it is common to explain impairment in terms of a limited processing capacity. Specifically, weakness in one domain of language processing in a limited capacity system might theoretically bleed resources from another area, causing this second domain to suffer as well. However, numerous researchers have emphasized the fundamental flaw in limited processing system hypotheses: such a theory is too broad to make substantive, testable predictions (see discussions by Bishop, 1992; Hill, 2001; Johnston, 1994) and thus is incapable of driving research on child development forward. Theories of cognitive trade-offs present the same problem: without a neurological/developmental framework to predict a pattern of trade-offs, such theories cannot be tested empirically, and as such are of little value to the child. Mortimer (2007) provides an analysis of processing trade-off theories with respect to articulation and language in SSD (see Panagos & Prelock, 1982; Panagos, Quine, & Klich, 1979), with reference to Dromey and Bates (2005). These latter authors, in an examination of bidirectional influences of speech and language performance suggest that tasks subserved within the same neurological region – presumably, that call upon similar neurological substrates – are more likely to show interference than tasks supported largely by distinct regions of the brain. 4.3. Limitations and future directions Although this study is unique in that it provides longitudinal data about the development of morphology and syntax in children with SSD, it is marked by some significant weaknesses that limit the interpretation of the results. First, the sample is small, with the group of children with persistently delayed morphological skills being particularly limited and thus it is possible that some of the statistical findings will prove to be unreliable due to sampling error. Second, an omnibus measure of language skills was not included as part of the assessment protocol and thus there are many aspects of language functioning that are not described in this report. Certain skills, such as receptive morphology skills for example, would be particularly important to target in future studies. Third, the children’s treatment experiences are unknown and thus it is not clear to what degree the content or intensity of the interventions that they received played a role in the outcomes that we observed when the children were in first grade. During the past half century the morphological skills of children with Specific Language Impairment have been a topic of intense research interest (Leonard et al., 2006; Marchman, Wulfeck, & Ellis Weismer, 1999; Oetting &

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Horohov, 1997; Rice & Wexler, 1996). This and other preliminary studies have shown that morphological deficits are characteristic of children with SSD while clearly demonstrating that these children’s morphological skills are not a direct reflection of their speech production errors (Haskill & Tyler, 2007; Rvachew et al., 2005). Recent research strongly suggests that the phenotypic signature of a heritable language impairment is in fact the presence of difficulties with speech production (Bishop & Hayiou-Thomas, 2008). In a study on articulation and language among children with SSD, Lewis et al. (2006a) discuss a general verbal trait deficit model of SSD in which multiple phenotypes may arise among members of a single family due the family member’s unique inheritance of risk genes and their specific environmental experience. It is now time to design larger scale studies to uncover the underlying biological and environmental factors that may link speech production and morphological deficits and to explain individual differences in recovery from these impairments. Acknowledgements This research was supported by the Canadian Language and Literacy Research Network and the Centre for Research on Language, Mind and Brain. We thank the families who participated in this project, as well as the Speech–Language Pathologists at the Alberta Children’s Hospital and the Children’s Hospital of Eastern Ontario for their assistance with recruitment of children. Gratitude is extended to the following students for their contributions to data collection and processing: Genevieve Cloutier, Myra Cox, Marie Desmarteau, Meghann Grawburg, Natalia Evans, Joan Heyding, Debbie Hughes, Catherine Norsworthy, Alyssa Ohberg, Alysha Serviss, and Rishanthi Sivakumaran. We would like to acknowledge in particular the work done by Pi-Yu Chiang in the reliability analyses of transcripts. Thanks are also owed to Dr. Jose Correa for statistics advice. Appendix A. Continuing education 1. Characteristics that might be useful in identifying 5-year-old children with Speech Sound Disorders at risk for poor expressive language outcomes are: (a) Poor receptive vocabulary in addition to poor MLU. (b) Poor receptive vocabulary in addition to poor finite verb morphology. (c) Poor MLU in addition to poor finite verb morphology. (d) Poor receptive vocabulary. (e) Poor MLU. 2. Children with SSD matched on MLU to children with typical development have been shown to be likely to have: (a) Low MLU, finite verb morphology score, and proportion of finite embedded clauses. (b) Low finite verb morphology score and low proportion of finite and non-finite embedded clauses. (c) Low developmental sentence score and low proportion of finite and non-finite embedded clauses. (d) Low finite verb morphology score, developmental sentence score, and proportion of finite embedded clauses. (e) Low finite verb morphology score, developmental sentence score, and proportion of finite and non-finite embedded clauses. 3. Although recent research has shown finite verb morphology to be problematic for pre-school children with SSD, poor performance in this area is largely the result of surface articulation difficulties with specific, word-final phonemes: T/F. 4. The relationship between SSD and SLI: (a) Cannot be definitively categorized given the evidence to date. (b) Suggests a large overlap between the two populations. (c) Suggests a slight overlap between the two populations. (d) Indicates a large overlap between the two populations given that they are the two forms of developmental language disorder uniquely associated with finite verb morphology difficulties. (e) Indicates a slight overlap between the two populations given that deficits in finite verb morphology tend to be more severe among individuals with SLI. 5. The children with SSD in this study had low finite embedded clause scores at pre-kindergarten, but this is likely due to scoring points subtracted for failure to mark verb morphemes: T/F.

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