- Email: [email protected]
Language comprehension in preschoolers with autism spectrum disorders without intellectual disability: Use of the Reynell Developmental Language Scales
Research in Autism Spectrum Disorders 6 (2012) 1119–1125
Contents lists available at SciVerse ScienceDirect
Research in Autism Spectrum Disorders Journal homepage: http://ees.elsevier.com/RASD/default.asp
Language comprehension in preschoolers with autism spectrum disorders without intellectual disability: Use of the Reynell Developmental Language Scales Liselotte Kjellmer a,b,c,*, A˚sa Hedvall a,d, Anette Holm d, Elisabeth Fernell a, Christopher Gillberg a, Fritjof Norrelgen a,b a
Gillberg Neuropsychiatry Centre, Sahlgrenska Academy, Gothenburg, Sweden Department of Speech and Language Pathology, Karolinska University Hospital, Stockholm, Sweden CLINTEC/Division of Speech Language Pathology, Karolinska Institutet, Stockholm, Sweden d Department of Psychology, Karolinska University Hospital, Stockholm, Sweden b c
A R T I C L E I N F O
A B S T R A C T
Article history: Received 29 February 2012 Accepted 6 March 2012
This study aimed to (a) assess language comprehension in children with autism spectrum disorders (ASD) without intellectual disability, (b) assess differences between ASD diagnostic subgroups, and (c) analyze the relationship between language comprehension and performance and verbal IQ, respectively. The 94 participants (83 boys, 11 girls; 4:0– 6:8 years) were a subgroup of a large cohort of 208 Swedish preschool children with ASD that had been followed longitudinally over 2 years. The Comprehension Scale of the Reynell Developmental Language Scales III (RDLS) was used at follow-up to assess language comprehension. Results revealed a delay in the development of language comprehension as well as high variability within the group as a whole. The Asperger syndrome and the Autistic feature groups performed within the normal range whereas the PDD-NOS and the Autistic disorder groups performed at the lower boundary of the normal range. However, importantly, 38% or more of the children showed results in the impaired range (i.e., <10th percentile) regardless of ASD type. Explained variance in language comprehension scores were 10% for non-verbal and 41% for verbal IQ. Many children with ASD without intellectual disability may have difficulties comprehending instructions in the classroom and in other everyday situations. The results highlight the need for detailed linguistic assessment of children with ASD. ß 2012 Elsevier Ltd. All rights reserved.
Keywords: Autism spectrum disorder Language comprehension Reynell Developmental Language Scales Preschool children
1. Introduction Although qualitative impairments in communication is one of the main criteria for autistic disorder in DSM-IV (APA, 1994), it is only in recent years that the heterogeneity of linguistic ability in children with autism spectrum disorder (ASD) has become increasingly recognized and researched (Eigsti, de Marchena, Schuh, & Kelly, 2011; Groen, Zwiers, van der Gaag, & Buitelaar, 2008; Kjelgaard & Tager-Flusberg, 2001). Yet, compared to a general consensus about certain unusual language characteristics being a major clinical feature of ASD, the nature of the general language abilities in children with ASD, especially among those without intellectual disability (ID), is relatively less understood (Chan, Cheung, Leung, Cheung, & Cheung, 2005). Language skills seem to be very variable in the ASD population, across the IQ spectrum (Chan et al., 2005;
* Corresponding author at: Astrid Lindgren Children’s Hospital Q2:05, Karolinska University Hospital, 171 76 Stockholm, Sweden. Tel.: +46 8 517 705 91. E-mail address: [email protected] (L. Kjellmer). 1750-9467/$ – see front matter ß 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.rasd.2012.03.003
1120
L. Kjellmer et al. / Research in Autism Spectrum Disorders 6 (2012) 1119–1125
Kjelgaard & Tager-Flusberg, 2001; Kjellmer, Hedvall, Fernell, Gillberg, & Norrelgen, 2012). Further, for those children without ID, researchers are investigating whether there might be a subgroup of children who show concomitant language impairment (LI), clinically similar to that of children with so-called specific language impairment (SLI; Kjelgaard & TagerFlusberg, 2001). In order to learn more about the language profiles displayed by children with ASD and IQ in the non-retarded range, additional data on their performance on different language subdomains and functions are needed from large, representative samples. Language comprehension is one such function that needs to be considered. Language comprehension is a broad construct that includes several linguistic and cognitive aspects. Here, we will focus on how children with ASD comprehend words and, in particular, sentences. In general, when considering the whole IQ spectrum, including children with and without ID, language comprehension in children with ASD seems to be delayed and strongly related to general cognitive ability. For single word comprehension, such results have been found for young children as measured by parent report (e.g., Charman, Drew, Baird, & Baird, 2003; Kjellmer et al., 2012; Luyster, Lopez, & Lord, 2007) and for children in the preschool to school-age range as measured by formal tests (e.g., Kjelgaard & TagerFlusberg, 2001). For sentence comprehension, a similar pattern has been demonstrated using formal tests (e.g., Chan et al., 2005). When considering the group of children with ASD and general cognitive ability within the normal range, however, research results are mixed. Some studies have found good word and sentence comprehension abilities in this group. For example, A˚sberg (2010) showed adequate word and sentence comprehension ability in his sample of school-age children with ASD, and the group performed similarly to a control group matched on non-verbal cognitive ability. Contrary to these results, other researchers have demonstrated compromised comprehension abilities for these children. Lloyd, Paintin, and Botting (2006) revealed relatively low scores in a group of children with ASD, aged 5–10 years, on the receptive composite score of the omnibus language test the Clinical Evaluation of Language Fundamentals (CELF; Semel, Wiig, & Secord, 1992, 1995). The CELF receptive composite includes, but is not restricted to, subtests on word and sentence comprehension. Chan et al. (2005) used the Token Test (Benton, Hamsher, & Sivan, 1994) to evaluate sentence comprehension in 5- to 6-year-old children with autism. When they examined a subgroup of their children with autism, whose non-verbal IQ scores were matched with those of the typically developing children in the control group, the children with ASD performed considerably lower (although not statistically significant) on verbal comprehension than controls. In the group without ID, type of ASD diagnosis has been indicated to play a role in determining level of language comprehension, such that children with Asperger syndrome (AS) would perform better than children with Autistic disorder and normal general cognitive ability (sometimes labeled ‘‘high-functioning autism’’, HFA). For example, comparing schoolage children with AS and HFA, Noterdaeme, Wriedt, and Ho¨hne (2010) rated the children’s receptive language (defined as word and sentence comprehension) as age-appropriate, moderately delayed/deviant, or clearly delayed/deviant. Indeed, the HFA group showed significantly more deficits in receptive language than the AS group. Using the verbal comprehension scale of the Reynell Developmental Language Scales (RDLS; Reynell & Huntley, 1987), which mainly assesses comprehension of sentences with increasing complexity, Szatmari, Archer, Fisman, Streiner, and Wilson (1995) reported that a group of children with HFA obtained lower scores than a group of children with AS, aged 4–6 years. The difference between groups remained even after controlling for IQ. However, contradicting these results, Ramberg, Ehlers, Nyde´n, Johansson, and Gillberg (1996) did not find statistically significant differences on the RDLS between their AS and HFA groups (children aged 5–15 years). Hence, for the group with ASD and IQ in the non-retarded range, results regarding language comprehension are inconsistent. In recent years, researchers have highlighted this variability and proposed two subgroups within the group of children with ASD without ID: those with concomitant LI and those without. For example, based on a broad range of language measures (receptive and expressive), Kjelgaard and Tager-Flusberg (2001) concluded that among the children with autistic disorder in their sample, who could complete the language tests used (most of whom had normal or low normal IQ, although some exhibited IQ scores in the retarded range), several had impaired language skills but some performed within the normal range. Moreover, the language profile of the children with impaired language was similar to that of children with SLI. Among children with ASD and concomitant LI many, though not all, may be expected to have language comprehension problems. Perhaps it should be noted here that LI can encompass expressive problems only, receptive problems only (relatively rare) or mixed expressive–receptive problems. Lindgren, Folstein, Tomblin, and Tager-Flusberg (2009) compared the language of school-age children with ASD with or without concomitant LI (most of whom had a full-scale IQ within the non-retarded range). Not surprisingly, the ASD + LI group scored significantly lower on a measure of word comprehension. When Chan et al. (2005) classified their 5- to 6-year-old children with autism and non-verbal IQ >70 as language impaired or not, about half of the group exhibited language skills within the normal range, one fourth exhibited impaired expression as well as comprehension skills, and one fourth exhibited normal comprehension but impaired expression (none showed the reversed pattern). In addition, Noterdaeme et al. (2010) showed that deviant language, including compromised comprehension, can be found in both in HFA and in AS. Indeed, more than 30% of the children with AS in their sample were found to have language problems, particularly in the receptive domain. For children with ASD without ID, their general cognitive ability may thus not be highly predictive of possible language comprehension problems. Indeed, based on their results, Kjelgaard and Tager-Flusberg (2001) noted that language skills can be independent of IQ in autism, and Chan et al. (2005) stated that although the language skills varied a lot in their sample of children with autism, the variability could not ‘‘simply be attributed to differences in general intelligence’’ (p. 123). Hence, general cognitive ability does not seem to be as prominent of an explaining factor for predicting language comprehension
L. Kjellmer et al. / Research in Autism Spectrum Disorders 6 (2012) 1119–1125
1121
ability in this group as when considering ASD across the whole IQ spectrum, or as when considering the very early receptive vocabulary development. In summary, the research results on language comprehension abilities in children with ASD without ID are equivocal. Methodologies between studies differ, making comparisons difficult. Different tests are used and study samples are often small or cover a wide age interval. Studies often do not include the whole ASD spectrum. Moreover, the study groups sometimes include children with lower cognitive abilities as well and results on tests of language comprehension are oftentimes not specified in detailed. The aim of this study was therefore to examine language comprehension in a large representative group of young children with ASD without ID within the narrow age range of 4–6 years. To assess language comprehension we used the receptive scale of a newer version of the RDLS, the Reynell Developmental Language Scales III (Edwards et al., 1997), which mainly assesses comprehension of sentences with increasing length and grammatical complexity. The RDLS is clinically commonly used in Europe and may be appealing to use with children with neurodevelopmental disabilities since it includes concrete objects as well as pictures. To date, the authors have found only two studies that have examined language comprehension with the RDLS in young children with ASD without ID (Ramberg et al., 1996; Szatmari et al., 1995). However, these studies reported age equivalent scores or developmental quotient scores (which are based on age equivalent scores) instead of standard scores and children with PDD-NOS were not included in the samples. Moreover, in both studies an older version of the RDLS was used and in the Szatmari study RDLS data were not reported in detail. Our study posed the following research questions: In children with ASD without ID: (a) What does language comprehension – as measured with the RDLS – look like? (b) Is there a difference between ASD diagnostic subgroups? and (c) What is the relation to performance and verbal IQ level? 2. Methods 2.1. Participants Participants were a subgroup of a large representative research cohort of 208 Swedish preschool children with autism spectrum disorders followed longitudinally over 2 years. The cohort is described in detail in Fernell et al. (2010, 2011). The 208 children had been referred to a special habilitation center, the Autism Center for Young Children (ACYC), in the Stockholm County before or at the age of 4.5 years. Research data were collected at the intake at ACYC (Time 1) and at followup 2 years later (Time 2). In this study, research data from Time 2 was used. Participants for the current investigation were selected from this larger sample on the basis of research psychologist testing at Time 2 confirming intelligence within the normal range based on a full scale IQ (FSIQ) 70 as measured by the Wechsler Preschool and Primary Scales of Intelligence III (WPPSI III; Wechsler, 1999, 2004). Two of the children were assessed elsewhere and deemed to be clearly within the normal range; however, exact IQ scores were not available. Results of two children in the larger sample fell just below the IQ limit; however, based on overall clinical assessment, including adaptive functioning, these children were not considered to fulfill criteria for mild intellectual disability and were thus included in the current study group. Seven children did not take part in the language testing at follow-up. The resulting study group of 94 children consisted of 83 boys and 11 girls, and the group’s mean FSIQ (n = 92) was 87.5 (SD 12.3). At the time of language testing, the chronological age range of the sample was 48–80 months (i.e., 4:0–6:8 years) with a mean age of 69 months (5:9 years; SD = 8.5 months). The language testing was administered close in time to the cognitive testing. ASD classifications in the study group at follow-up presented as follows: autistic disorder (AD; 23%, n = 22), PDD-NOS (47%, n = 44), Asperger syndrome (13%, n = 12), and autistic features (17%, n = 16). In the ASD diagnostic process at follow-up, a group of children turned out to not qualify for a definite ASD diagnosis any longer. Their clinical profile was more compatible with ‘‘autistic features’’ (see Fernell et al., 2011). Table 1 shows the distribution of IQ scores per type of ASD. 2.2. Measures and procedures Language testing at Time 2 was administered by two research speech-language pathologists and included a battery of different tests. The total time of language testing was approximately 1.5–2 h. Here, the results of language comprehension as measured by the comprehension scale of the Reynell Developmental Language Scales III (RDLS; Edwards et al., 1997) will be presented. The RDLS was the first test administered for all children.
Table 1 Mean IQ scores for each diagnostic subgroup.
AD (n 22) PDD-NOS (n 44) Asperger syndrome (n 12) Autistic features (n 16)
Full scale IQ
Verbal IQ
Performance IQ
82.0 86.3 95.7 92.1
81.7 85.9 99.0 92.7
89.9 97.4 102.0 101.1
(12.1) (11.3) (14.7) (9.0)
(14.4) (13.7) (13.2) (9.2)
(14.9) (14.3) (19.0) (11.6)
1122
L. Kjellmer et al. / Research in Autism Spectrum Disorders 6 (2012) 1119–1125
Table 2 Reynell percentile scores for each diagnostic group.
AD (n 22) PDD-NOS (n 44) Asperger syndrome (n 12) Autistic features (n 16)
Mean
Min.
Max.
14.0 17.0 36.4 40.1
1.0 1.0 1.0 1.0
86.0 88.0 92.0 93.0
(22.2) (23.1) (36.5) (34.4)
Table 3 Proportion of children with Reynell score below the 10th percentile and at 1st percentile per diagnostic group.
AD (n 22) PDD-NOS (n 44) Asperger syndrome (n 12) Autistic features (n 16)
10th percentile
1st percentile
64% 64% 42% 38%
50% 25% 17% 13%
The RDLS includes some items that concern single word comprehension; however, most items assess the comprehension of sentences that include abstract verbal concepts, increasingly complex grammatical structures, and a few sentences that require inference. The RDLS manual gives an option to omit the early items on single word comprehension (15 items) if the tester has sufficient evidence to assume that the child would score at ceiling for the first sections. Since all children in this study were assessed by the research psychologists to have an IQ in the non-retarded range, all children were given a score of 15 for these items. At the time of the study, Swedish reference values did not exist for the age-range of our study group; thus, British norms were used. This procedure is commonly used in both research and clinical practice in a small language like Swedish. However, proper caution should of course be taken when interpreting these standard scores. 2.3. Data analysis Descriptive data analysis used percentile scores since those are clinically relevant for the RDLS. Inferential data analyses were based on z-scores, derived from RDLS T-scores, instead of percentile scores to achieve a less skewed distribution. The transformation from T-scores to z-scores was conducted for ease of interpretation. Differences in RDLS results between ASD subgroups were analyzed using Analysis of Variance (ANOVA) and correlations between RDLS scores and performance IQ (PIQ) and verbal IQ (VIQ) scores, respectively, were analyzed using Pearson’s correlation coefficients. Since exact IQ scores were missing for two children, correlations between RDLS scores and IQ scores were based on 92 children. 3. Results 3.1. Descriptive data analysis In general, results based on RDLS percentile scores revealed a delay in the development of language comprehension as well as high variability within the group as a whole (M = 22.7, SD = 28.6). Table 2 shows that the Asperger syndrome group as well as the Autistic feature group fell within the normal range. The PDD-NOS group and the AD group performed at the lower boundary of the normal range. Fifty-six percent of the whole group had a language comprehension score below the 10th percentile, i.e., a score in the impaired range. Table 3 presents the proportion of children with an RDLS score below the 10th percentile per ASD subgroup. As can be seen, 38% or more of the children showed results in the impaired range regardless of ASD classification. Table 3 also presents the proportion of children with an RDLS score at the 1st percentile per ASD subgroup. While the highest proportion was found in the AD group, cases were spread between all ASD subgroups (AD – 11 cases; PDD-NOS – 11 cases; Asperger syndrome – 2 cases; autistic features – 2 cases). Of the total group, 28% of the children had such a low score. 3.2. Inferential data analysis Descriptive analysis indicated mean differences between the autistic features and Asperger syndrome groups compared to the two other ASD subgroups (see Fig. 1). Between-groups analysis of variance based on z-scores showed significant differences between groups, F(3, 90) = 4.15, p = .008. Post hoc analysis (Tukey’s) revealed that the differences pertained to the Autistic disorder group performing significantly lower than the autistic features group (p = .039) and the Asperger syndrome group (p = .037), respectively. Figs. 2 and 3 show scatter plots of RDLS z-scores in relation to PIQ and VIQ scores, respectively. The correlation between RDLS scores (z-scores) and PIQ scores was significant (Pearson’s r = .31, p = .002); however, only 10% (r2) of the variation in language comprehension scores within the ASD group could be explained by PIQ. The correlation between RDLS scores
L. Kjellmer et al. / Research in Autism Spectrum Disorders 6 (2012) 1119–1125
1123
Fig. 1. Results on RDLS (z-scores) divided by diagnostic subgroups. The box plots represent median (line), 25th and 75th percentiles (box), and min. and max. values (whiskers).
Fig. 2. Scatter plot of each child’s RDLS score (z-score) in relation to the PIQ score.
(z-scores) and VIQ was higher (Pearson’s r = .64, p = <.001), still only 41% (r2) of the variation in language comprehension scores could be explained by VIQ. 4. Discussion This is the first study to present detailed data on language comprehension as measured by the RDLS in a reasonably large, representative group of children between 4 and 6 years of age with ASD without ID. Results revealed compromised language comprehension for the majority of the children, which conforms with the results of for example Lloyd et al. (2006) and Chan et al. (2005), but contrasts with the results of A˚sberg (2010). Not surprisingly, in our sample the Asperger syndrome group and the Autistic feature group performed significantly better than the AD group, with the results of the PDD-NOS group falling in between. Likewise, both Noterdaeme et al. (2010) and Szatmari et al. (1995) found that children with AS in general showed better language comprehension than children with HFA (in our study, the ‘‘AD group’’ is comparable to what others
1124
L. Kjellmer et al. / Research in Autism Spectrum Disorders 6 (2012) 1119–1125
Fig. 3. Scatter plot of each child’s RDLS score (z-score) in relation to the VIQ score.
describe as HFA). Ramberg et al. (1996) did not find significant differences in language comprehension between children with AS and HFA, perhaps due to low statistical power. Perhaps more importantly, however, several studies have found impaired language comprehension in children without ID regardless of type of ASD diagnosis (Chan et al., 2005; Kjelgaard & Tager-Flusberg, 2001; Noterdaeme et al., 2010). In our study, a result below the 10th percentile was considered as falling in the impaired range, a commonly used cut-off (Leonard, 1998). Overall, 56% of the children showed impaired language comprehension. The proportion was highest in the AD and PDD-NOS groups (64% in each); yet, even in the Asperger group 42% of the children performed in the impaired range. These results correspond to the findings of others. For example, using the receptive composite score of the CELF, Lloyd et al. (2006) found that 40% of their 5- to 10-year-old children with ASD scored 1SD below the mean or lower (e.g., 16th percentile). Noterdaeme et al. (2010) reported that a total of 76% of their school-age children (6–19 years) with HFA and 39% of their children with Asperger syndrome had moderately to clearly delayed/deviant receptive language. Examining the language of 5- to 6-year-old children with autism, Chan et al. (2005) classified 27% of the children who had a non-verbal IQ >70 as having impaired comprehension skills. Although these studies have used different methodologies to assess language comprehension, all have found that a high proportion of the children with ASD without ID, including children with Asperger syndrome, exhibited impaired language comprehension as in our study. On the flipside of the coin, a considerable proportion of the children in the current study had a normal performance on the RDLS, regardless of ASD classification. Likewise, other studies have demonstrated that some children with ASD, including children with a diagnosis of autistic disorder, without ID have no receptive or expressive language difficulties (e.g., Chan et al., 2005; Kjelgaard & Tager-Flusberg, 2001; Noterdaeme et al., 2010). A striking finding of our study was the low explanatory value (r2 = 10%) of PIQ on the variance in RDLS-III scores. In other words, our data indicate that the language comprehension, especially as it pertains to comprehension of sentences, of children with ASD without ID oftentimes cannot be predicted by performance/non-verbal IQ. In the field of LI studies, a discrepancy criterion is often used when diagnosing so-called SLI. This criterion is often defined as a discrepancy between actual expressive and/or receptive language level (as measured by formal language tests) and expected language level based on non-verbal IQ (Leonard, 1998). Moreover, sometimes a cut-off of a non-verbal IQ no less than 85 is used in order to diagnose SLI to ensure that the children are not generally delayed in their development (Leonard, 1998). In our sample, 37 children with a PIQ 85 (i.e., well within the normal range) performed within the impaired range (i.e., below the 10th percentile) on the RDLS (see Fig. 2). Thus, even though it was not the purpose of this study to identify children with LI and we have not yet analyzed expressive language data for our children, we assume that some of them could be described as having a concomitant LI, perhaps with a language profile clinically commensurate with that of so-called SLI, as proposed by Kjelgaard and Tager-Flusberg (2001). Further, in many studies concerning language abilities in children with ASD, performance/non-verbal IQ has been used as a matching variable when equating experimental and control groups. This might involve some methodological concerns. For example, children with non-verbal abilities exceeding verbal comprehension abilities will be disadvantaged when comparing language comprehension to children developing typically, which is also discussed by Jarrold, Boucher, and Russell (1997). On the other hand, children with verbal comprehension abilities exceeding their non-verbal abilities will have an advantage over their matched peers. The interpretation of study results may thus potentially be misleading. The explanatory value of VIQ on the variance in RDLS-III scores in our study was also relatively low (r2 = 41%). This implies that for children with ASD without ID language comprehension cannot be predicted by verbal IQ to such a high degree as one might have expected. One explanation of the low correlation could be that the verbal subscales of the WIPPSI include items that
L. Kjellmer et al. / Research in Autism Spectrum Disorders 6 (2012) 1119–1125
1125
test both receptive and expressive language, whereas the comprehension subscale of the RDLS tests receptive language only. In our sample, 17 children with a verbal IQ 85 (i.e., well within the normal range) performed within the impaired range (i.e., below the 10th percentile) on the RDLS (see Fig. 3). As discussed before, impaired language comprehension could be a sign of LI. Clinically, children with a good verbal IQ may nonetheless show language difficulties leading to a diagnosis of LI. Perhaps then, some children with ASD and good verbal IQ may still show language difficulties commensurate with a concomitant LI. Limitations of this study include the rather small diagnostic subgroups, in particular the Asperger syndrome and Autistic feature groups. The children in the Asperger syndrome group in our sample were identified at an early age. Commonly, however, children are diagnosed with Asperger syndrome at school age. Thus, the conclusions drawn based on our sample may not be generalizable to children diagnosed at a later age. Another limitation is the use of British norms for the RDLS. However, this is a commonly used procedure in both research and in clinical practice with regard to languages such as Swedish which is spoken by a limited number of people. Thus, proper caution should be taken when interpreting these standard scores. In conclusion, our study shows that many children with ASD without ID have impaired language comprehension. Moreover, the variability in language comprehension is only explained to a relatively low degree by VIQ and to an even lower degree by PIQ. This highlights the need for detailed linguistic assessment of this group of children, which has also been pointed out by Lloyd et al. (2006). Indeed, detailed knowledge of a child’s language skills may be a significant factor both in understanding the current functioning and for the long-term prognosis of the child with ASD (Bennett et al., 2008; Ventner, Lord, & Schoppler, 1992). Another clinical implication of the data from this study is that many of these children may have difficulties comprehending instructions in everyday situations as well as teacher instructions in the classroom. The latter point is important since many children with ASD without ID are mainstreamed in regular classrooms. Moreover, according to our clinical experience many parents of children with ASD claim that their children ‘‘understand everything’’. Formal language testing may, however, reveal that the child’s context independent language comprehension is not within the ageappropriate range. Therefore, assessing language comprehension in children with ASD is an important task for speechlanguage pathologists. Such information can make important contributions in tailoring and adapting teaching and intervention strategies to meet the individual child’s specific needs. References American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (DSM-IV) (4th ed.). Washington, DC: American Psychiatric Association. A˚sberg, J. (2010). Patterns of language and discourse comprehension skills in school-aged children with autism spectrum disorders. Scandinavian Journal of Psychology, 51, 534–539. Bennett, T., Szatmari, P., Bryson, S., Volden, J., Zwaigenbaum, L., Vaccarella, L., et al. (2008). Differentiating autism and Asperger syndrome on the basis of language delay or impairment. Journal of Autism and Developmental Disorders, 38, 616–625. Multilingual aphasia examination. (1994). (3rd ed.). Iowa: AJA Associates. Chan, A. S., Cheung, J., Leung, W. W. M., Cheung, R., & Cheung, M.-C. (2005). Verbal expression and comprehension deficits in young children with autism. Focus on Autism and Other Developmental Disabilities, 20, 117–124. Charman, T., Drew, A., Baird, C., & Baird, G. (2003). Measuring early language development in preschool children with autism spectrum disorder using the MacArthur Communicative Development Inventory (infant form). Journal of Child Language, 30, 213–236. Edwards, S., Fletcher, P., Garman, M., Hughes, A., Letts, C., & Sinka, I. (1997). The Reynell Developmental Language Scales III. Windsor/Berks, UK: The nferNelson Publishing Company Ltd. Eigsti, I.-M., de Marchena, A. B., Schuh, J., & Kelly, E. (2011). Language acquisition in autism spectrum disorders: A developmental review. Research in Autism Spectrum Disorders, 5, 681–691. Fernell, E., Hedvall, A., Norrelgen, F., Eriksson, M., Hoglund-Carlsson, L., Barnevik-Olsson, M., et al. (2010). Developmental profiles in preschool children with autism spectrum disorders referred for intervention. Research in Developmental Disabilities, 31(3), 790–799. Fernell, E., Hedvall, A., Westerlund, J., Ho¨glund Carlsson, L., Eriksson, M., Barnevik-Olsson, M., et al. (2011). Early intervention in 208 preschoolers with autism spectrum disorder. A prospective naturalistic study. Research in Developmental Disabilities, 36(6), 2092–2101. Groen, W. B., Zwiers, M. P., van der Gaag, R. J., & Buitelaar, J. K. (2008). The phenotype and neural correlates of language in autism: An integrative review. Neuroscience and Biobehavioral Reveiws, 32(8), 1416–1425. Jarrold, C., Boucher, J., & Russell, J. (1997). Language profiles in children with autism: Theoretical and methodological implications. Autism, 1, 57–76. Kjelgaard, M. M., & Tager-Flusberg, H. (2001). An investigation of language impairment in autism: Implications for genetic subgroups. Language and Cognitive Processes, 16(2-3), 287–308. Kjellmer, L., Hedvall, A˚. , Fernell, E., Gillberg, C., & Norrelgen, F. (2012). Language and communication skills in preschool children with autism spectrum disorders: Contribution of cognition, severity of autism symptoms, and adaptive functioning to the variability. Research in Developmental Disabilities, 33(1), 172–180. Leonard, L. (1998). Children with specific language impairment. Cambridge: Massachusetts Institute of Technology Press. Lindgren, K. A., Folstein, S. E., Tomblin, B. J., & Tager-Flusberg, H. (2009). Language and reading abilities of children with autism spectrum disorders and specific language impairment and their first-degree relatives. Autism Research, 2, 22–38. Lloyd, H., Paintin, K., & Botting, N. (2006). Performance of children with different types of communication impairment on the Clinical Evaluation of Language Fundamentals (CELF). Child Language Teaching and Therapy, 22(1), 47–67. Luyster, R., Lopez, K., & Lord, C. (2007). Characterizing communicative development in children referred for autism spectrum disorders using the MacArthur-Bates Communicative Development Inventory (CDI). Journal of Child Language, 34(3), 623–654. Noterdaeme, M., Wriedt, E., & Ho¨hne, C. (2010). Asperger’s syndrome and high-functioning autism: Language, motor and cognitive profiles. European Child and Adolescent Psychiatry, 19, 475–481. Ramberg, C., Ehlers, S., Nyde´n, A., Johansson, M., & Gillberg, C. (1996). Language and pragmatic functions in school-age children on the autism spectrum. A comparative study of 55 boys. European Journal of Disorders of Communication, 31, 387–414. Reynell, J., & Huntley, M. (1987). Reynell developmental language scales manual. Windsor/England: NFER-Nelson. Semel, E. M., Wiig, E. H., & Secord, W. (1992). Clinical Evaluation of Language Fundamentals – Preschool. The Psychological Corporation. Semel, E. M., Wiig, E. H., & Secord, W. (1995). Clinical Evaluation of Language Fundamentals – Revised UK3. The Psychological Corporation. Szatmari, P., Archer, L., Fisman, S., Streiner, D. L., & Wilson, F. (1995). Asperger’s syndrome and autism: Differences in behavior, cognition, and adaptive functioning. Journal of the American Academy of Child & Adolescent Psychiatry, 34(12), 1662–1671. Ventner, A., Lord, C., & Schoppler, E. (1992). A follow-up study of high-functioning autistic children. Journal of Child Psychology and Psychiatry, 33, 489–507. Wechsler, D. (1999, 2004). Wechsler preschool and primary scale of intelligence, revised, Swedish version. Stockholm: Psykologifo¨rlaget.
Contents lists available at SciVerse ScienceDirect
Research in Autism Spectrum Disorders Journal homepage: http://ees.elsevier.com/RASD/default.asp
Language comprehension in preschoolers with autism spectrum disorders without intellectual disability: Use of the Reynell Developmental Language Scales Liselotte Kjellmer a,b,c,*, A˚sa Hedvall a,d, Anette Holm d, Elisabeth Fernell a, Christopher Gillberg a, Fritjof Norrelgen a,b a
Gillberg Neuropsychiatry Centre, Sahlgrenska Academy, Gothenburg, Sweden Department of Speech and Language Pathology, Karolinska University Hospital, Stockholm, Sweden CLINTEC/Division of Speech Language Pathology, Karolinska Institutet, Stockholm, Sweden d Department of Psychology, Karolinska University Hospital, Stockholm, Sweden b c
A R T I C L E I N F O
A B S T R A C T
Article history: Received 29 February 2012 Accepted 6 March 2012
This study aimed to (a) assess language comprehension in children with autism spectrum disorders (ASD) without intellectual disability, (b) assess differences between ASD diagnostic subgroups, and (c) analyze the relationship between language comprehension and performance and verbal IQ, respectively. The 94 participants (83 boys, 11 girls; 4:0– 6:8 years) were a subgroup of a large cohort of 208 Swedish preschool children with ASD that had been followed longitudinally over 2 years. The Comprehension Scale of the Reynell Developmental Language Scales III (RDLS) was used at follow-up to assess language comprehension. Results revealed a delay in the development of language comprehension as well as high variability within the group as a whole. The Asperger syndrome and the Autistic feature groups performed within the normal range whereas the PDD-NOS and the Autistic disorder groups performed at the lower boundary of the normal range. However, importantly, 38% or more of the children showed results in the impaired range (i.e., <10th percentile) regardless of ASD type. Explained variance in language comprehension scores were 10% for non-verbal and 41% for verbal IQ. Many children with ASD without intellectual disability may have difficulties comprehending instructions in the classroom and in other everyday situations. The results highlight the need for detailed linguistic assessment of children with ASD. ß 2012 Elsevier Ltd. All rights reserved.
Keywords: Autism spectrum disorder Language comprehension Reynell Developmental Language Scales Preschool children
1. Introduction Although qualitative impairments in communication is one of the main criteria for autistic disorder in DSM-IV (APA, 1994), it is only in recent years that the heterogeneity of linguistic ability in children with autism spectrum disorder (ASD) has become increasingly recognized and researched (Eigsti, de Marchena, Schuh, & Kelly, 2011; Groen, Zwiers, van der Gaag, & Buitelaar, 2008; Kjelgaard & Tager-Flusberg, 2001). Yet, compared to a general consensus about certain unusual language characteristics being a major clinical feature of ASD, the nature of the general language abilities in children with ASD, especially among those without intellectual disability (ID), is relatively less understood (Chan, Cheung, Leung, Cheung, & Cheung, 2005). Language skills seem to be very variable in the ASD population, across the IQ spectrum (Chan et al., 2005;
* Corresponding author at: Astrid Lindgren Children’s Hospital Q2:05, Karolinska University Hospital, 171 76 Stockholm, Sweden. Tel.: +46 8 517 705 91. E-mail address: [email protected] (L. Kjellmer). 1750-9467/$ – see front matter ß 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.rasd.2012.03.003
1120
L. Kjellmer et al. / Research in Autism Spectrum Disorders 6 (2012) 1119–1125
Kjelgaard & Tager-Flusberg, 2001; Kjellmer, Hedvall, Fernell, Gillberg, & Norrelgen, 2012). Further, for those children without ID, researchers are investigating whether there might be a subgroup of children who show concomitant language impairment (LI), clinically similar to that of children with so-called specific language impairment (SLI; Kjelgaard & TagerFlusberg, 2001). In order to learn more about the language profiles displayed by children with ASD and IQ in the non-retarded range, additional data on their performance on different language subdomains and functions are needed from large, representative samples. Language comprehension is one such function that needs to be considered. Language comprehension is a broad construct that includes several linguistic and cognitive aspects. Here, we will focus on how children with ASD comprehend words and, in particular, sentences. In general, when considering the whole IQ spectrum, including children with and without ID, language comprehension in children with ASD seems to be delayed and strongly related to general cognitive ability. For single word comprehension, such results have been found for young children as measured by parent report (e.g., Charman, Drew, Baird, & Baird, 2003; Kjellmer et al., 2012; Luyster, Lopez, & Lord, 2007) and for children in the preschool to school-age range as measured by formal tests (e.g., Kjelgaard & TagerFlusberg, 2001). For sentence comprehension, a similar pattern has been demonstrated using formal tests (e.g., Chan et al., 2005). When considering the group of children with ASD and general cognitive ability within the normal range, however, research results are mixed. Some studies have found good word and sentence comprehension abilities in this group. For example, A˚sberg (2010) showed adequate word and sentence comprehension ability in his sample of school-age children with ASD, and the group performed similarly to a control group matched on non-verbal cognitive ability. Contrary to these results, other researchers have demonstrated compromised comprehension abilities for these children. Lloyd, Paintin, and Botting (2006) revealed relatively low scores in a group of children with ASD, aged 5–10 years, on the receptive composite score of the omnibus language test the Clinical Evaluation of Language Fundamentals (CELF; Semel, Wiig, & Secord, 1992, 1995). The CELF receptive composite includes, but is not restricted to, subtests on word and sentence comprehension. Chan et al. (2005) used the Token Test (Benton, Hamsher, & Sivan, 1994) to evaluate sentence comprehension in 5- to 6-year-old children with autism. When they examined a subgroup of their children with autism, whose non-verbal IQ scores were matched with those of the typically developing children in the control group, the children with ASD performed considerably lower (although not statistically significant) on verbal comprehension than controls. In the group without ID, type of ASD diagnosis has been indicated to play a role in determining level of language comprehension, such that children with Asperger syndrome (AS) would perform better than children with Autistic disorder and normal general cognitive ability (sometimes labeled ‘‘high-functioning autism’’, HFA). For example, comparing schoolage children with AS and HFA, Noterdaeme, Wriedt, and Ho¨hne (2010) rated the children’s receptive language (defined as word and sentence comprehension) as age-appropriate, moderately delayed/deviant, or clearly delayed/deviant. Indeed, the HFA group showed significantly more deficits in receptive language than the AS group. Using the verbal comprehension scale of the Reynell Developmental Language Scales (RDLS; Reynell & Huntley, 1987), which mainly assesses comprehension of sentences with increasing complexity, Szatmari, Archer, Fisman, Streiner, and Wilson (1995) reported that a group of children with HFA obtained lower scores than a group of children with AS, aged 4–6 years. The difference between groups remained even after controlling for IQ. However, contradicting these results, Ramberg, Ehlers, Nyde´n, Johansson, and Gillberg (1996) did not find statistically significant differences on the RDLS between their AS and HFA groups (children aged 5–15 years). Hence, for the group with ASD and IQ in the non-retarded range, results regarding language comprehension are inconsistent. In recent years, researchers have highlighted this variability and proposed two subgroups within the group of children with ASD without ID: those with concomitant LI and those without. For example, based on a broad range of language measures (receptive and expressive), Kjelgaard and Tager-Flusberg (2001) concluded that among the children with autistic disorder in their sample, who could complete the language tests used (most of whom had normal or low normal IQ, although some exhibited IQ scores in the retarded range), several had impaired language skills but some performed within the normal range. Moreover, the language profile of the children with impaired language was similar to that of children with SLI. Among children with ASD and concomitant LI many, though not all, may be expected to have language comprehension problems. Perhaps it should be noted here that LI can encompass expressive problems only, receptive problems only (relatively rare) or mixed expressive–receptive problems. Lindgren, Folstein, Tomblin, and Tager-Flusberg (2009) compared the language of school-age children with ASD with or without concomitant LI (most of whom had a full-scale IQ within the non-retarded range). Not surprisingly, the ASD + LI group scored significantly lower on a measure of word comprehension. When Chan et al. (2005) classified their 5- to 6-year-old children with autism and non-verbal IQ >70 as language impaired or not, about half of the group exhibited language skills within the normal range, one fourth exhibited impaired expression as well as comprehension skills, and one fourth exhibited normal comprehension but impaired expression (none showed the reversed pattern). In addition, Noterdaeme et al. (2010) showed that deviant language, including compromised comprehension, can be found in both in HFA and in AS. Indeed, more than 30% of the children with AS in their sample were found to have language problems, particularly in the receptive domain. For children with ASD without ID, their general cognitive ability may thus not be highly predictive of possible language comprehension problems. Indeed, based on their results, Kjelgaard and Tager-Flusberg (2001) noted that language skills can be independent of IQ in autism, and Chan et al. (2005) stated that although the language skills varied a lot in their sample of children with autism, the variability could not ‘‘simply be attributed to differences in general intelligence’’ (p. 123). Hence, general cognitive ability does not seem to be as prominent of an explaining factor for predicting language comprehension
L. Kjellmer et al. / Research in Autism Spectrum Disorders 6 (2012) 1119–1125
1121
ability in this group as when considering ASD across the whole IQ spectrum, or as when considering the very early receptive vocabulary development. In summary, the research results on language comprehension abilities in children with ASD without ID are equivocal. Methodologies between studies differ, making comparisons difficult. Different tests are used and study samples are often small or cover a wide age interval. Studies often do not include the whole ASD spectrum. Moreover, the study groups sometimes include children with lower cognitive abilities as well and results on tests of language comprehension are oftentimes not specified in detailed. The aim of this study was therefore to examine language comprehension in a large representative group of young children with ASD without ID within the narrow age range of 4–6 years. To assess language comprehension we used the receptive scale of a newer version of the RDLS, the Reynell Developmental Language Scales III (Edwards et al., 1997), which mainly assesses comprehension of sentences with increasing length and grammatical complexity. The RDLS is clinically commonly used in Europe and may be appealing to use with children with neurodevelopmental disabilities since it includes concrete objects as well as pictures. To date, the authors have found only two studies that have examined language comprehension with the RDLS in young children with ASD without ID (Ramberg et al., 1996; Szatmari et al., 1995). However, these studies reported age equivalent scores or developmental quotient scores (which are based on age equivalent scores) instead of standard scores and children with PDD-NOS were not included in the samples. Moreover, in both studies an older version of the RDLS was used and in the Szatmari study RDLS data were not reported in detail. Our study posed the following research questions: In children with ASD without ID: (a) What does language comprehension – as measured with the RDLS – look like? (b) Is there a difference between ASD diagnostic subgroups? and (c) What is the relation to performance and verbal IQ level? 2. Methods 2.1. Participants Participants were a subgroup of a large representative research cohort of 208 Swedish preschool children with autism spectrum disorders followed longitudinally over 2 years. The cohort is described in detail in Fernell et al. (2010, 2011). The 208 children had been referred to a special habilitation center, the Autism Center for Young Children (ACYC), in the Stockholm County before or at the age of 4.5 years. Research data were collected at the intake at ACYC (Time 1) and at followup 2 years later (Time 2). In this study, research data from Time 2 was used. Participants for the current investigation were selected from this larger sample on the basis of research psychologist testing at Time 2 confirming intelligence within the normal range based on a full scale IQ (FSIQ) 70 as measured by the Wechsler Preschool and Primary Scales of Intelligence III (WPPSI III; Wechsler, 1999, 2004). Two of the children were assessed elsewhere and deemed to be clearly within the normal range; however, exact IQ scores were not available. Results of two children in the larger sample fell just below the IQ limit; however, based on overall clinical assessment, including adaptive functioning, these children were not considered to fulfill criteria for mild intellectual disability and were thus included in the current study group. Seven children did not take part in the language testing at follow-up. The resulting study group of 94 children consisted of 83 boys and 11 girls, and the group’s mean FSIQ (n = 92) was 87.5 (SD 12.3). At the time of language testing, the chronological age range of the sample was 48–80 months (i.e., 4:0–6:8 years) with a mean age of 69 months (5:9 years; SD = 8.5 months). The language testing was administered close in time to the cognitive testing. ASD classifications in the study group at follow-up presented as follows: autistic disorder (AD; 23%, n = 22), PDD-NOS (47%, n = 44), Asperger syndrome (13%, n = 12), and autistic features (17%, n = 16). In the ASD diagnostic process at follow-up, a group of children turned out to not qualify for a definite ASD diagnosis any longer. Their clinical profile was more compatible with ‘‘autistic features’’ (see Fernell et al., 2011). Table 1 shows the distribution of IQ scores per type of ASD. 2.2. Measures and procedures Language testing at Time 2 was administered by two research speech-language pathologists and included a battery of different tests. The total time of language testing was approximately 1.5–2 h. Here, the results of language comprehension as measured by the comprehension scale of the Reynell Developmental Language Scales III (RDLS; Edwards et al., 1997) will be presented. The RDLS was the first test administered for all children.
Table 1 Mean IQ scores for each diagnostic subgroup.
AD (n 22) PDD-NOS (n 44) Asperger syndrome (n 12) Autistic features (n 16)
Full scale IQ
Verbal IQ
Performance IQ
82.0 86.3 95.7 92.1
81.7 85.9 99.0 92.7
89.9 97.4 102.0 101.1
(12.1) (11.3) (14.7) (9.0)
(14.4) (13.7) (13.2) (9.2)
(14.9) (14.3) (19.0) (11.6)
1122
L. Kjellmer et al. / Research in Autism Spectrum Disorders 6 (2012) 1119–1125
Table 2 Reynell percentile scores for each diagnostic group.
AD (n 22) PDD-NOS (n 44) Asperger syndrome (n 12) Autistic features (n 16)
Mean
Min.
Max.
14.0 17.0 36.4 40.1
1.0 1.0 1.0 1.0
86.0 88.0 92.0 93.0
(22.2) (23.1) (36.5) (34.4)
Table 3 Proportion of children with Reynell score below the 10th percentile and at 1st percentile per diagnostic group.
AD (n 22) PDD-NOS (n 44) Asperger syndrome (n 12) Autistic features (n 16)
10th percentile
1st percentile
64% 64% 42% 38%
50% 25% 17% 13%
The RDLS includes some items that concern single word comprehension; however, most items assess the comprehension of sentences that include abstract verbal concepts, increasingly complex grammatical structures, and a few sentences that require inference. The RDLS manual gives an option to omit the early items on single word comprehension (15 items) if the tester has sufficient evidence to assume that the child would score at ceiling for the first sections. Since all children in this study were assessed by the research psychologists to have an IQ in the non-retarded range, all children were given a score of 15 for these items. At the time of the study, Swedish reference values did not exist for the age-range of our study group; thus, British norms were used. This procedure is commonly used in both research and clinical practice in a small language like Swedish. However, proper caution should of course be taken when interpreting these standard scores. 2.3. Data analysis Descriptive data analysis used percentile scores since those are clinically relevant for the RDLS. Inferential data analyses were based on z-scores, derived from RDLS T-scores, instead of percentile scores to achieve a less skewed distribution. The transformation from T-scores to z-scores was conducted for ease of interpretation. Differences in RDLS results between ASD subgroups were analyzed using Analysis of Variance (ANOVA) and correlations between RDLS scores and performance IQ (PIQ) and verbal IQ (VIQ) scores, respectively, were analyzed using Pearson’s correlation coefficients. Since exact IQ scores were missing for two children, correlations between RDLS scores and IQ scores were based on 92 children. 3. Results 3.1. Descriptive data analysis In general, results based on RDLS percentile scores revealed a delay in the development of language comprehension as well as high variability within the group as a whole (M = 22.7, SD = 28.6). Table 2 shows that the Asperger syndrome group as well as the Autistic feature group fell within the normal range. The PDD-NOS group and the AD group performed at the lower boundary of the normal range. Fifty-six percent of the whole group had a language comprehension score below the 10th percentile, i.e., a score in the impaired range. Table 3 presents the proportion of children with an RDLS score below the 10th percentile per ASD subgroup. As can be seen, 38% or more of the children showed results in the impaired range regardless of ASD classification. Table 3 also presents the proportion of children with an RDLS score at the 1st percentile per ASD subgroup. While the highest proportion was found in the AD group, cases were spread between all ASD subgroups (AD – 11 cases; PDD-NOS – 11 cases; Asperger syndrome – 2 cases; autistic features – 2 cases). Of the total group, 28% of the children had such a low score. 3.2. Inferential data analysis Descriptive analysis indicated mean differences between the autistic features and Asperger syndrome groups compared to the two other ASD subgroups (see Fig. 1). Between-groups analysis of variance based on z-scores showed significant differences between groups, F(3, 90) = 4.15, p = .008. Post hoc analysis (Tukey’s) revealed that the differences pertained to the Autistic disorder group performing significantly lower than the autistic features group (p = .039) and the Asperger syndrome group (p = .037), respectively. Figs. 2 and 3 show scatter plots of RDLS z-scores in relation to PIQ and VIQ scores, respectively. The correlation between RDLS scores (z-scores) and PIQ scores was significant (Pearson’s r = .31, p = .002); however, only 10% (r2) of the variation in language comprehension scores within the ASD group could be explained by PIQ. The correlation between RDLS scores
L. Kjellmer et al. / Research in Autism Spectrum Disorders 6 (2012) 1119–1125
1123
Fig. 1. Results on RDLS (z-scores) divided by diagnostic subgroups. The box plots represent median (line), 25th and 75th percentiles (box), and min. and max. values (whiskers).
Fig. 2. Scatter plot of each child’s RDLS score (z-score) in relation to the PIQ score.
(z-scores) and VIQ was higher (Pearson’s r = .64, p = <.001), still only 41% (r2) of the variation in language comprehension scores could be explained by VIQ. 4. Discussion This is the first study to present detailed data on language comprehension as measured by the RDLS in a reasonably large, representative group of children between 4 and 6 years of age with ASD without ID. Results revealed compromised language comprehension for the majority of the children, which conforms with the results of for example Lloyd et al. (2006) and Chan et al. (2005), but contrasts with the results of A˚sberg (2010). Not surprisingly, in our sample the Asperger syndrome group and the Autistic feature group performed significantly better than the AD group, with the results of the PDD-NOS group falling in between. Likewise, both Noterdaeme et al. (2010) and Szatmari et al. (1995) found that children with AS in general showed better language comprehension than children with HFA (in our study, the ‘‘AD group’’ is comparable to what others
1124
L. Kjellmer et al. / Research in Autism Spectrum Disorders 6 (2012) 1119–1125
Fig. 3. Scatter plot of each child’s RDLS score (z-score) in relation to the VIQ score.
describe as HFA). Ramberg et al. (1996) did not find significant differences in language comprehension between children with AS and HFA, perhaps due to low statistical power. Perhaps more importantly, however, several studies have found impaired language comprehension in children without ID regardless of type of ASD diagnosis (Chan et al., 2005; Kjelgaard & Tager-Flusberg, 2001; Noterdaeme et al., 2010). In our study, a result below the 10th percentile was considered as falling in the impaired range, a commonly used cut-off (Leonard, 1998). Overall, 56% of the children showed impaired language comprehension. The proportion was highest in the AD and PDD-NOS groups (64% in each); yet, even in the Asperger group 42% of the children performed in the impaired range. These results correspond to the findings of others. For example, using the receptive composite score of the CELF, Lloyd et al. (2006) found that 40% of their 5- to 10-year-old children with ASD scored 1SD below the mean or lower (e.g., 16th percentile). Noterdaeme et al. (2010) reported that a total of 76% of their school-age children (6–19 years) with HFA and 39% of their children with Asperger syndrome had moderately to clearly delayed/deviant receptive language. Examining the language of 5- to 6-year-old children with autism, Chan et al. (2005) classified 27% of the children who had a non-verbal IQ >70 as having impaired comprehension skills. Although these studies have used different methodologies to assess language comprehension, all have found that a high proportion of the children with ASD without ID, including children with Asperger syndrome, exhibited impaired language comprehension as in our study. On the flipside of the coin, a considerable proportion of the children in the current study had a normal performance on the RDLS, regardless of ASD classification. Likewise, other studies have demonstrated that some children with ASD, including children with a diagnosis of autistic disorder, without ID have no receptive or expressive language difficulties (e.g., Chan et al., 2005; Kjelgaard & Tager-Flusberg, 2001; Noterdaeme et al., 2010). A striking finding of our study was the low explanatory value (r2 = 10%) of PIQ on the variance in RDLS-III scores. In other words, our data indicate that the language comprehension, especially as it pertains to comprehension of sentences, of children with ASD without ID oftentimes cannot be predicted by performance/non-verbal IQ. In the field of LI studies, a discrepancy criterion is often used when diagnosing so-called SLI. This criterion is often defined as a discrepancy between actual expressive and/or receptive language level (as measured by formal language tests) and expected language level based on non-verbal IQ (Leonard, 1998). Moreover, sometimes a cut-off of a non-verbal IQ no less than 85 is used in order to diagnose SLI to ensure that the children are not generally delayed in their development (Leonard, 1998). In our sample, 37 children with a PIQ 85 (i.e., well within the normal range) performed within the impaired range (i.e., below the 10th percentile) on the RDLS (see Fig. 2). Thus, even though it was not the purpose of this study to identify children with LI and we have not yet analyzed expressive language data for our children, we assume that some of them could be described as having a concomitant LI, perhaps with a language profile clinically commensurate with that of so-called SLI, as proposed by Kjelgaard and Tager-Flusberg (2001). Further, in many studies concerning language abilities in children with ASD, performance/non-verbal IQ has been used as a matching variable when equating experimental and control groups. This might involve some methodological concerns. For example, children with non-verbal abilities exceeding verbal comprehension abilities will be disadvantaged when comparing language comprehension to children developing typically, which is also discussed by Jarrold, Boucher, and Russell (1997). On the other hand, children with verbal comprehension abilities exceeding their non-verbal abilities will have an advantage over their matched peers. The interpretation of study results may thus potentially be misleading. The explanatory value of VIQ on the variance in RDLS-III scores in our study was also relatively low (r2 = 41%). This implies that for children with ASD without ID language comprehension cannot be predicted by verbal IQ to such a high degree as one might have expected. One explanation of the low correlation could be that the verbal subscales of the WIPPSI include items that
L. Kjellmer et al. / Research in Autism Spectrum Disorders 6 (2012) 1119–1125
1125
test both receptive and expressive language, whereas the comprehension subscale of the RDLS tests receptive language only. In our sample, 17 children with a verbal IQ 85 (i.e., well within the normal range) performed within the impaired range (i.e., below the 10th percentile) on the RDLS (see Fig. 3). As discussed before, impaired language comprehension could be a sign of LI. Clinically, children with a good verbal IQ may nonetheless show language difficulties leading to a diagnosis of LI. Perhaps then, some children with ASD and good verbal IQ may still show language difficulties commensurate with a concomitant LI. Limitations of this study include the rather small diagnostic subgroups, in particular the Asperger syndrome and Autistic feature groups. The children in the Asperger syndrome group in our sample were identified at an early age. Commonly, however, children are diagnosed with Asperger syndrome at school age. Thus, the conclusions drawn based on our sample may not be generalizable to children diagnosed at a later age. Another limitation is the use of British norms for the RDLS. However, this is a commonly used procedure in both research and in clinical practice with regard to languages such as Swedish which is spoken by a limited number of people. Thus, proper caution should be taken when interpreting these standard scores. In conclusion, our study shows that many children with ASD without ID have impaired language comprehension. Moreover, the variability in language comprehension is only explained to a relatively low degree by VIQ and to an even lower degree by PIQ. This highlights the need for detailed linguistic assessment of this group of children, which has also been pointed out by Lloyd et al. (2006). Indeed, detailed knowledge of a child’s language skills may be a significant factor both in understanding the current functioning and for the long-term prognosis of the child with ASD (Bennett et al., 2008; Ventner, Lord, & Schoppler, 1992). Another clinical implication of the data from this study is that many of these children may have difficulties comprehending instructions in everyday situations as well as teacher instructions in the classroom. The latter point is important since many children with ASD without ID are mainstreamed in regular classrooms. Moreover, according to our clinical experience many parents of children with ASD claim that their children ‘‘understand everything’’. Formal language testing may, however, reveal that the child’s context independent language comprehension is not within the ageappropriate range. Therefore, assessing language comprehension in children with ASD is an important task for speechlanguage pathologists. Such information can make important contributions in tailoring and adapting teaching and intervention strategies to meet the individual child’s specific needs. References American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (DSM-IV) (4th ed.). Washington, DC: American Psychiatric Association. A˚sberg, J. (2010). Patterns of language and discourse comprehension skills in school-aged children with autism spectrum disorders. Scandinavian Journal of Psychology, 51, 534–539. Bennett, T., Szatmari, P., Bryson, S., Volden, J., Zwaigenbaum, L., Vaccarella, L., et al. (2008). Differentiating autism and Asperger syndrome on the basis of language delay or impairment. Journal of Autism and Developmental Disorders, 38, 616–625. Multilingual aphasia examination. (1994). (3rd ed.). Iowa: AJA Associates. Chan, A. S., Cheung, J., Leung, W. W. M., Cheung, R., & Cheung, M.-C. (2005). Verbal expression and comprehension deficits in young children with autism. Focus on Autism and Other Developmental Disabilities, 20, 117–124. Charman, T., Drew, A., Baird, C., & Baird, G. (2003). Measuring early language development in preschool children with autism spectrum disorder using the MacArthur Communicative Development Inventory (infant form). Journal of Child Language, 30, 213–236. Edwards, S., Fletcher, P., Garman, M., Hughes, A., Letts, C., & Sinka, I. (1997). The Reynell Developmental Language Scales III. Windsor/Berks, UK: The nferNelson Publishing Company Ltd. Eigsti, I.-M., de Marchena, A. B., Schuh, J., & Kelly, E. (2011). Language acquisition in autism spectrum disorders: A developmental review. Research in Autism Spectrum Disorders, 5, 681–691. Fernell, E., Hedvall, A., Norrelgen, F., Eriksson, M., Hoglund-Carlsson, L., Barnevik-Olsson, M., et al. (2010). Developmental profiles in preschool children with autism spectrum disorders referred for intervention. Research in Developmental Disabilities, 31(3), 790–799. Fernell, E., Hedvall, A., Westerlund, J., Ho¨glund Carlsson, L., Eriksson, M., Barnevik-Olsson, M., et al. (2011). Early intervention in 208 preschoolers with autism spectrum disorder. A prospective naturalistic study. Research in Developmental Disabilities, 36(6), 2092–2101. Groen, W. B., Zwiers, M. P., van der Gaag, R. J., & Buitelaar, J. K. (2008). The phenotype and neural correlates of language in autism: An integrative review. Neuroscience and Biobehavioral Reveiws, 32(8), 1416–1425. Jarrold, C., Boucher, J., & Russell, J. (1997). Language profiles in children with autism: Theoretical and methodological implications. Autism, 1, 57–76. Kjelgaard, M. M., & Tager-Flusberg, H. (2001). An investigation of language impairment in autism: Implications for genetic subgroups. Language and Cognitive Processes, 16(2-3), 287–308. Kjellmer, L., Hedvall, A˚. , Fernell, E., Gillberg, C., & Norrelgen, F. (2012). Language and communication skills in preschool children with autism spectrum disorders: Contribution of cognition, severity of autism symptoms, and adaptive functioning to the variability. Research in Developmental Disabilities, 33(1), 172–180. Leonard, L. (1998). Children with specific language impairment. Cambridge: Massachusetts Institute of Technology Press. Lindgren, K. A., Folstein, S. E., Tomblin, B. J., & Tager-Flusberg, H. (2009). Language and reading abilities of children with autism spectrum disorders and specific language impairment and their first-degree relatives. Autism Research, 2, 22–38. Lloyd, H., Paintin, K., & Botting, N. (2006). Performance of children with different types of communication impairment on the Clinical Evaluation of Language Fundamentals (CELF). Child Language Teaching and Therapy, 22(1), 47–67. Luyster, R., Lopez, K., & Lord, C. (2007). Characterizing communicative development in children referred for autism spectrum disorders using the MacArthur-Bates Communicative Development Inventory (CDI). Journal of Child Language, 34(3), 623–654. Noterdaeme, M., Wriedt, E., & Ho¨hne, C. (2010). Asperger’s syndrome and high-functioning autism: Language, motor and cognitive profiles. European Child and Adolescent Psychiatry, 19, 475–481. Ramberg, C., Ehlers, S., Nyde´n, A., Johansson, M., & Gillberg, C. (1996). Language and pragmatic functions in school-age children on the autism spectrum. A comparative study of 55 boys. European Journal of Disorders of Communication, 31, 387–414. Reynell, J., & Huntley, M. (1987). Reynell developmental language scales manual. Windsor/England: NFER-Nelson. Semel, E. M., Wiig, E. H., & Secord, W. (1992). Clinical Evaluation of Language Fundamentals – Preschool. The Psychological Corporation. Semel, E. M., Wiig, E. H., & Secord, W. (1995). Clinical Evaluation of Language Fundamentals – Revised UK3. The Psychological Corporation. Szatmari, P., Archer, L., Fisman, S., Streiner, D. L., & Wilson, F. (1995). Asperger’s syndrome and autism: Differences in behavior, cognition, and adaptive functioning. Journal of the American Academy of Child & Adolescent Psychiatry, 34(12), 1662–1671. Ventner, A., Lord, C., & Schoppler, E. (1992). A follow-up study of high-functioning autistic children. Journal of Child Psychology and Psychiatry, 33, 489–507. Wechsler, D. (1999, 2004). Wechsler preschool and primary scale of intelligence, revised, Swedish version. Stockholm: Psykologifo¨rlaget.