This study investigated the relationship between pragmatic ability and two aspects of structural language in conversational language samples from 24 school-age children with and without high-functioning autism (HFA): causal statements and speech disruptions. In contrast to a majority of previous studies, grammatical complexity and mean length of utterance were factored into the analyses, since these are potential confounding variables. The results showed that children with HFA used fewer spontaneous causal statements and fewer filled pauses in conversation compared to children with typical development (TD). There was also a significant and positive relationship between filled pauses and pragmatic ability after controlling for structural language ability. The results may help us understand the conversational patterns of children with HFA better.
Language sample analysis (LSA) provides the opportunity to study a child’s language skills in a naturalistic context (e.g., conversation or narratives) and many researchers have advocated for LSA as a substitute or complement to standardized testing of children with communication difficulties [
In the current study, conversational language samples from school-age children with high-functioning autism (HFA) and their TD peers are analyzed. Children with HFA score within normal range on standardized measures of structural language and nonverbal intelligence but show communication difficulties originating from pragmatic difficulties. This group comprises a small part of all individuals with autism (<5%) [
As mentioned previously, children with HFA are not expected to show differences in many of the standard LSA measures that have been found to differentiate children with SLI from TD peers. Several studies have confirmed this: if individuals on the autism spectrum are matched with TD peers on structural language skills, there are no significant differences between groups in, for example, overall grammatical complexity [
The first aim of the present study is to investigate the relationship between pragmatic ability and causal statements in conversation, while controlling for grammatical complexity. Causal statements are a measure of interest since limited use can be interpreted from a pragmatic perspective, in that the underlying reason could be a lack of sensitivity to listener interests and needs. For example, when a child says
Causal language has mainly been explored in picture-elicited narratives from children and adults with HFA and not in conversation. A conversation places a set of different pragmatic demands on the participant in terms of both speaking and listening, such as turn-taking and topic management [
The second aim of the present study is to investigate speech disruptions in conversation and their relationship to pragmatic ability, while explicitly reporting and factoring in utterance length in the analyses. Speech disruptions, or mazes, include revisions or self-repairs, self-repetitions, and filled pauses (e.g.,
Studies analyzing conversational samples from children with TD and HFA have found that children with HFA exhibit fewer filled pauses compared to their peers, but these studies have failed to report MLU or grammatical complexity, which means that the results could be a consequence of less complex language rather than pragmatic difficulties [
The direct relationship between pragmatic ability and speech disruptions has only been explored in one previous study [
In summary, previous studies are inconclusive, and it remains uncertain whether children with HFA show less use of causal language and filled pauses due to their pragmatic difficulties or due to overall less complex language in their language samples. Therefore, the current study will analyze conversational language samples and relate the severity of pragmatic difficulties to causal language and speech disruptions use, while taking language complexity into account. This study is guided by the following questions and corresponding hypotheses: Do two groups of children that vary in their pragmatic skills but are matched on structural language skills (children with HFA and children with TD) differ in terms of
their spontaneous use of causal language in conversation? the proportion of filled pauses in conversation? While taking structural language ability into account, is pragmatic ability (measured by the CCC-2) associated with
the proportion of causal statements in conversation? the proportion of filled pauses and repetition/revisions in conversation?
Children with HFA are predicted to show a significantly smaller proportion of spontaneous causal language use and fewer filled pauses in conversation compared to their TD peers based on the hypothesized pragmatic functions of causal statements and filled pauses (satisfying listener needs of details and explanations and holding the floor between speaker turns, resp.). The groups are not predicted to differ in their grammatical complexity or in their proportion of revisions and repetitions. In addition, pragmatic ability is predicted to be positively and significantly correlated with independent causal statements and filled pauses but not correlated with repetitions and revisions.
Informed oral consent to participate in the study was obtained from all participating children, and written consent was obtained from the caregivers according to a protocol approved by the New York University Committee on Activities Involving Human Subjects.
Seven children with HFA (2 girls, 5 boys) and 17 children with TD (12 girls, 5 boys) were recruited from the same public schools in the New York area, both from regular classrooms and inclusive classrooms for children with high-functioning autism (the Nest Program). The Nest Program follows the normal academic curriculum in integrated classrooms with fewer students and more adult support. The students are given additional instructional and behavioral support, as well as regular speech-language therapy.
All children were in the second or third grade (ages 7 : 1 to 9 : 2). Children with TD had no history or signs of developmental or academic delays according to parents and teachers. Children with HFA had all received a diagnosis of an autism spectrum disorder (as determined by the ADOS [
All children were given the
Means and standard deviations of typically developing children (TD,
Children with HFA | Children with TD | Group difference | |
---|---|---|---|
Mean (SD), range | Mean (SD), range | ||
Age in months | 93.6 (9.33), 85–113 | 98.1 (5.41), 87–107 | n.s. |
TOLD standard score | 102.4 (14.56), 85–122 | 106.1 (11.09), 87–129 | n.s. |
TONI standard score | 102.0 (8.66), 97–121 | 106.7 (19.25), 85–150 | n.s. |
CCC-2 pragmatic composite | 21.0 (6.90), 12–29 |
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The child’s caregiver was asked to complete the
Each child met individually with a trained research assistant (a graduate speech-language pathology student) in a quiet room at the child’s school. The child participated in two sessions, approximately 45 minutes each, which included a structured conversational language task (described below), the battery of standardized tests, and other discourse tasks unrelated to the present study. The structured conversational task was conducted at the beginning of the first session. The children were video-recorded for the duration of the sessions.
The structured conversational task required each child to talk for approximately 10 minutes with the experimenter, following a protocol with interview questions about topics including family, interests, and events, as well as some open-ended questions in an attempt to control for variation in conversational content. The experimenter provided a model by sharing information about, for example, her family and favorite things and then asked the child to do the same. The experimenter was allowed to give as much verbal and nonverbal support as needed, and focus was on creating a natural conversational context while at the same time eliciting a sufficiently long language sample from the child. A similar protocol has been suggested by Hadley [
Language samples were transcribed orthographically by the first and second authors and by three trained research assistants and analyzed using the software SALT (Systematic Analysis of Language Transcripts) [
C-units and P-units are two different methods of segmenting a transcript into utterances. Segmentation into C-units is based on grammatical rules, where each C-unit contains one independent clause and all its dependent clauses, which is in contrast to P-units, where intonation and pauses are used to determine the completion of an utterance. C-units reflect grammatical complexity to a higher extent and have been shown to be more reliable across transcribers, while P-units reflect the actual length of a spoken utterance to a larger extent [
For all analyses, elliptical and imitative responses, as well as yes-no replies, were excluded so that these types of short utterances did not deflate the mean utterance length (MLPU2) [
The measures included in the causal language analyses were clausal density and independent and solicited causal statements. Clausal density was included as a direct measure of syntactic complexity. Clausal density is the total number of clauses (main + dependent) per main clause. Main and dependent clauses were coded to calculate density, following the procedure used by Nippold et al. [
The measures included in the analyses of speech disruptions were MLPU2, revisions and repetitions, filled pauses, and total speech disruptions.
Speech disruptions were divided into two categories: revisions/repetitions and filled pauses [
Reliability testing was carried out in three steps: reliability of transcription, reliability of segmentation in C-units and P-units, and reliability of coding.
16% of the recordings were retranscribed, and interrater reliability was determined by number of words in agreement, including all speech disruptions. Agreement was computed by dividing the total number of words in agreement by the total number of words in the transcript. Average agreement was 95.4% (range 92.9–97.9%). All disagreements in the reliability transcriptions were solved through discussion. A graduate student, who was blind to the diagnostic status of the children, segmented the transcripts in C-units and P-units and calculated MLPU2. She also recoded those transcripts for clausal density, causal language, and examiner prompts for causal language. Reliability for number of C-units was 98.6% and number of P-units was 96.7%, calculated as percent agreement on raw numbers. Correlations showed that reliability of MLPU2 was
SPSS 23 was used for all statistical analyses. Independent samples
Before analyzing causal language use, we examined the length (complete and intelligible C-units) of the language samples of the two groups (see Table
Descriptive data for number of C-units, clausal density, and causal language of children with HFA (
Children with HFA | Children with TD | |||
---|---|---|---|---|
Mean (SD) | Range | Mean (SD) | Range | |
Total number of C-units | 80.9 (20.13) | 43–128 | 99.3 (30.24) | 51–136 |
Clausal density | 1.15 (0.0792) | 1.03–1.27 | 1.22 (0.0801) | 1.07–1.33 |
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0.013 (0.010) | 0–0.02 | 0.064 (0.046) | 0.01–0.18 |
Solicited causal statements/C-unit | 0.014 (0.010) | 0–0.03 | 0.023 (0.016) | 0–0.06 |
Number of “why” questions | 2.00 (1.414) | 1–4 | 1.82 (1.131) | 0–4 |
To investigate differences in the use of causal language, we examined clausal density, independent and solicited causal statements, and number of “Why” questions from the experimenter. Means and standard deviations of all measures are presented in Table
There were no significant differences between children with HFA and children with TD in clausal density,
To investigate group differences in the use of speech disruptions, we examined MLPU2, revisions and repetitions per P-unit, and filled pauses per P-unit. Means and standard deviations of all measures are presented in Table
Descriptive data for mean length of P-unit, revisions/repetitions, and filled pauses for children with HFA (
Children with HFA | Children with TD | |||
---|---|---|---|---|
Mean (SD) | Range | Mean (SD) | Range | |
MLPU2 | 7.61 (2.331) | 5.40–10.98 | 9.85 (1.998) | 6.96–13.46 |
Revisions and repetitions/P-unit | 0.36 (0.191) | 0.06–0.56 | 0.55 (0.371) | 0.05–1.36 |
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0.23 (0.205) | 0.03–0.59 | 0.46 (0.259) | 0.09–1.11 |
CCC-2 scores were missing for two of the children in the TD group; hence, the total number of participants included in correlations involving CCC-2 scores was 22 (7 children with HFA, 15 with TD).
A correlation between pragmatic scores and the number of independent causal statements per C-unit including all children yielded a small positive, but insignificant relationship,
To investigate the relationship between speech disruptions, MLPU2, TOLD composite score, and pragmatic scores, a series of bivariate correlations were carried out.
As expected, MLPU2 was significantly positively correlated with both filled pauses (
Pragmatic scores were significantly and positively correlated with filled pauses (
Table
Partial correlations between filled pauses, revisions/repetitions, MLPU2, and pragmatic scales. TOLD composite language scores are included as a covariate (
Sum of pragmatic scales | Filled pauses per P-unit | Revisions and repetitions per P-unit | |
---|---|---|---|
Sum of CCC-2 pragmatic scales | |||
Correlation ( |
|
.216 | |
|
.036 | .348 | |
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Mean length of P-unit (MLPU2) | |||
Correlation ( |
.401 |
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.072 | .003 | .000 |
This study investigated causal language and filled pauses in conversation in school-age children with high-functioning autism (HFA) and typical development (TD) and examined the relationship between pragmatic ability and these structural aspects of language. All children scored within normal range of standardized verbal and nonverbal tests, and groups did not differ significantly in age, composite language scores, nonverbal IQ, or language sample complexity. The differences between groups were therefore interpreted as a result of differences in pragmatic ability. To the authors’ knowledge, this is the first study that has found significant relationships while explicitly controlling for and reporting relevant structural language skills.
The results confirmed the first hypothesis: children with HFA showed less independent causal statements but a similar amount of solicited causal statements. This indicates that children with HFA provide the listener with solicited explanations to the same degree as their TD peers. In the absence of an explicit prompt, however, they tend to provide explanations to a lesser extent. The underlying reason might be a lower sensitivity to listener needs and/or an inability to follow cultural communicative conventions [
Although there was a significant difference between groups in the use of causal language, there was no significant relationship between pragmatic scores on the CCC-2 and independent causal language, which was not according to the hypothesis (a positive but nonsignificant relationship was found). It is possible that, with a larger group of children with HFA and increased power for statistical analysis, there might have been a significant relationship. It is also possible that the items in the CCC-2 quantify pragmatic ability more broadly, with the consequence that causal language is too specific and subtle of a feature of social/pragmatic ability to be linked to this measure. Development of complex language (including causal language) has been shown to be related to the development of theory of mind [
The results confirmed the hypothesis that children with HFA would demonstrate a significantly lower proportion of filled pauses (but not of revisions/repetitions) compared to TD children in conversation. The group difference in mean length of P-unit also approached significance, however (
Importantly, even after controlling for structural language ability as measured by the TOLD, the strong and positive relationship between MLPU2 and both fillers and revisions/repetitions held. This indicates that it is unlikely that fillers
This study was limited in sample size, but the analyses and matching between groups (both regarding age and structural language ability) were more rigorous than most previous studies. Further replication is needed to draw any firm conclusions, however. Conversation was judged to be the most appropriate speaking context to investigate the relationship between pragmatic ability and the chosen features of language production, but a more challenging speaking context might be included in future studies. Such contexts may include multiple speakers or tasks with persuasive or argumentative language. These contexts may tax children more, with a more explicit demand for holding the floor and taking several listeners’ needs into account. They may therefore be even more revealing from the perspective of studying language production from a pragmatic perspective.
The present study only investigated a few aspects of structural language and the relationship to pragmatic skills and did not investigate the content of the conversation. The effect of different content could be revealing, however, since children with ASD often have restricted interests. The interaction between conversational content and features of speech and language form may be quantified and investigated by focusing on repetitive topics in language samples. A recent study by Rouhizadeh et al. [
Finally, other groups of children also show pragmatic difficulties, including children with social communication disorder [
The results of this study indicate that children with HFA use significantly fewer independent causal statements and exhibit fewer fillers in conversation compared to peers with TD, in spite of equally strong performance on standardized language tests and similar grammatical complexity/MLU. This adds to the previous literature, which has found similar relationships, but has failed to control for structural language abilities. Research should continue to focus on dialogic naturalistic contexts instead of language tests, as language sampling from naturalistic contexts increases our understanding of how these children make use of language for purposeful communication. The difficulties that children with HFA have in conversation might be subtle, and standard LSA measures might not capture the characteristics, even though the quality of the interaction might be perceived as “different.” Less use of independent causal language places the burden of communication on the speaking partner, by requiring them to infer information or ask questions to a larger extent. Similarly, fewer fillers in conversation (with a possible increase in silent pauses as a consequence) may also make the natural back-and-forth in conversation more effortful for the typical conversational partner. A listener may perceive these characteristics as odd, even though the speaker’s structural language ability is within normal range. Thus, these findings may be used to increase our understanding of how children with HFA may behave in conversation and provide two measures that would be easy to implement in clinical practice. Causal language might also be a possible target in language intervention, with a focus on causal explanations in social discourse, as well as in personal narratives. Such approaches could possibly be carried out in tandem with a focus on increased self-awareness and awareness of listener needs in order to strengthen theory of mind skills [
14
Does not look at the person he or she is talking to.
48
Does not explain what he or she is talking about to someone who does not share his or her experiences (e.g., talks about “Johnny” without explaining who Johnny is).
56
Makes good use of gestures to get his or her meaning across.
60
Realizes the need to be polite (e.g., would act pleased if given a present he or she did not really like; would avoid making personal comments about strangers).
A main clause consists of a subject and a main verb and makes a complete statement. For example, the following utterances are both independent clauses: “I met a new friend today” and “He runs very fast through the forest.”
A dependent clause contains a subject and a main verb but does not make a complete statement (i.e., cannot stand alone). For example, “…who was singing in the shower.” There are three main types of subordinate clauses: nominal, adverbial, and relative. In the present study, all dependent clauses were coded and counted together.
Clausal density is calculated by adding all main and subordinate clauses in the sample and dividing this number by the total number of main clauses. The number obtained reflects the degree of subordination in the sample. An example:
All codes were placed at the end of an utterance. One utterance could not receive more than one causal language code. All instances of child causal statements including
An independent causal statement is a statement used without a soliciting question.
C: I like going to the beach because I like playing in the sand [CAU]. C: She wanted to go to the mall so she could buy a new doll [CAU].
A solicited causal statement follows a why-prompt from the experimenter, and both the prompt and the causal statement are coded.
C: I like dogs. E: Why do you like dogs [WHY]? C: Because they are fluffy [SCAU].
The authors declare that there are no competing interests regarding the publication of this paper.
Christina Reuterskiöld initially conceived the study, Anna Eva Hallin selected the features for analysis, collected and analyzed data, and wrote the manuscript together with Gabrielle D. Garcia, who also conducted part of the analyses. Christina Reuterskiöld participated in all of the processes through supervision, discussion, and review.
The authors express their gratitude to the children and parents who participated in the study from the schools in the NYU Steinhardt/New York City Department of Education ASD Nest Program and the Research Assistants in the CSD Department Small Talk Child Language Lab. The authors also extend their gratitude to Dr. Harriet Klein, Dr. Diana Sidtis, Dr. Susanne Quadflieg, and Dr. Diego Almeida for their comments on previous drafts of this paper. This study was supported by an NYU Steinhardt School Faculty Research Challenge Grant.