A Narrative Evaluation of Mandarin-Speaking Children With Language Impairment Purpose We aimed to study narrative skills in Mandarin-speaking children with language impairment (LI) to compare with children with LI speaking Indo-European languages. Method Eighteen Mandarin-speaking children with LI (mean age 6;2 [years;months]) and 18 typically developing (TD) age controls told 3 stories elicited using the Mandarin Expressive ... Research Article
Open Access
Research Article  |   February 15, 2018
A Narrative Evaluation of Mandarin-Speaking Children With Language Impairment
 
Author Affiliations & Notes
  • Ying Hao
    Shanghai Children's Medical Center Affiliated with the Medical School of Shanghai Jiao Tong University, China
    MOE-Shanghai Key Laboratory of Children's Environmental Health, China
    The University of Texas at Austin
  • Li Sheng
    Shanghai Children's Medical Center Affiliated with the Medical School of Shanghai Jiao Tong University, China
    MOE-Shanghai Key Laboratory of Children's Environmental Health, China
    University of Delaware, Newark
  • Yiwen Zhang
    Shanghai Children's Medical Center Affiliated with the Medical School of Shanghai Jiao Tong University, China
    MOE-Shanghai Key Laboratory of Children's Environmental Health, China
  • Fan Jiang
    Shanghai Children's Medical Center Affiliated with the Medical School of Shanghai Jiao Tong University, China
    MOE-Shanghai Key Laboratory of Children's Environmental Health, China
  • Jill de Villiers
    Smith College, Northampton, MA
    Bethel Hearing and Speaking Training Center, Farmers Branch, Corinth, TX
  • Wendy Lee
    Bethel Hearing and Speaking Training Center, Farmers Branch, Corinth, TX
    The University of Texas at Dallas
  • Xueman Lucy Liu
    Bethel Hearing and Speaking Training Center, Farmers Branch, Corinth, TX
    The University of Texas at Dallas
  • Disclosure: The narrative evaluation is under development as a test and the authors have financial interests in future royalties.
    Disclosure: The narrative evaluation is under development as a test and the authors have financial interests in future royalties. ×
  • Correspondence to Xueman Lucy Liu: lucy.liu@ourbethel.com
  • Editor-in-Chief: Sean Redmond
    Editor-in-Chief: Sean Redmond×
  • Editor: Janna Oetting
    Editor: Janna Oetting×
Article Information
Cultural & Linguistic Diversity / Language Disorders / Language / Research Articles
Research Article   |   February 15, 2018
A Narrative Evaluation of Mandarin-Speaking Children With Language Impairment
Journal of Speech, Language, and Hearing Research, February 2018, Vol. 61, 345-359. doi:10.1044/2017_JSLHR-L-16-0367
History: Received September 18, 2016 , Revised April 17, 2017 , Accepted August 28, 2017
 
Journal of Speech, Language, and Hearing Research, February 2018, Vol. 61, 345-359. doi:10.1044/2017_JSLHR-L-16-0367
History: Received September 18, 2016; Revised April 17, 2017; Accepted August 28, 2017

Purpose We aimed to study narrative skills in Mandarin-speaking children with language impairment (LI) to compare with children with LI speaking Indo-European languages.

Method Eighteen Mandarin-speaking children with LI (mean age 6;2 [years;months]) and 18 typically developing (TD) age controls told 3 stories elicited using the Mandarin Expressive Narrative Test (de Villiers & Liu, 2014). We compared macrostructure-evaluating descriptions of characters, settings, initiating events, internal responses,plans, actions, and consequences. We also studied general microstructure, including productivity, lexical diversity, syntactic complexity, and grammaticality. In addition, we compared the use of 6 fine-grained microstructure elements that evaluate particular Mandarin linguistic features.

Results Children with LI exhibited weaknesses in 5 macrostructure elements, lexical diversity, syntactic complexity, and 3 Mandarin-specific, fine-grained microstructure elements. Children with LI and TD controls demonstrated comparable performance on 2 macrostructure elements, productivity, grammaticality, and the remaining 3 fine-grained microstructure features.

Conclusions Similarities and differences are noted in narrative profiles of children with LI who speak Mandarin versus those who speak Indo-European languages. The results are consistent with the view that profiles of linguistic deficits are shaped by the ambient language. Clinical implications are discussed.

Considerable research regarding language impairment (LI) has been conducted with children speaking Indo-European languages, for example, English (e.g., Fey, Catts, Proctor-Williams, Tomblin, & Zhang, 2004), Swedish (e.g., Reuterskiöld, Hansson, & Sahlén, 2011), and Greek (e.g., Tsimpli, Peristeri, & Andreou, 2016). Compared to Indo-European languages, Chinese is a typologically distinct language. Grammatical features in Chinese are typically expressed by separate words, whereas in many Indo-European languages, they are expressed by affixes. The ambient language that a child with LI is exposed to greatly shapes areas of ease and difficulty (Leonard, 2014b). More than a quarter of the world's population speak Chinese (Yip & Matthews, 2010). As one of the most important Chinese languages, Mandarin is not well studied in the realm of LI (Leonard, 2014a). To equip Chinese speech-language pathologists with more accurate assessments and effective interventions, we first need to understand the linguistic weaknesses of Mandarin-speaking children with LI.
Narrative production incorporates various language components into a complete story. Narrative evaluation thus provides a rich description of children's expressive language. Assessing narrative production is informative in understanding language manifestations of children with LI. Using narrative analysis, previous studies have revealed multiple deficits in children with LI who speak Indo-European languages, including effects on the organization of complete and coherent stories, and the diversity and complexity of linguistic expressions (e.g., de Villiers, 2004; Reilly, Losh, Bellugi, & Wulfeck, 2004; Tsimpli et al., 2016).
To the best of our knowledge, only three studies (Cheung, 2009; Tsai & Chang, 2008; Zhang, 2009) evaluated narrative production in Mandarin-speaking children with LI. All of them had very small sample sizes (n ≤ 6). Though these studies revealed a number of difficulties in Mandarin-speaking children with LI, most of these findings have not been replicated. The current study intended to replicate and extend previous findings and identify weaknesses in Mandarin-speaking children with LI using a larger sample size.
Narrative evaluation typically comprises macro- and microstructure analyses (Gagarina, Klop, Tsimpli, & Walters, 2016; Justice, Bowles, Pence, & Gosse, 2010). Macrostructure measures the global organization of a story, including descriptions of characters, settings, initial events, characters' internal states and plans, actions, and consequences (Gillam, Gillam, Fargo, Olszewski, & Segura, 2017). Microstructure, however, takes into account fine-grained language-internal properties, such as the usage of different syntactic structures and specific types of words (Gorman, Bingham, Fiestas, & Terry, 2016; Justice et al., 2010). Microstructure evaluation also includes more general measures providing information about overall oral language productivity and complexity. For example, total number of utterances (TNU) and total number of words (TNW) reflect story length (Muñoz, Gillam, Peña, & Gulley-Faehnle, 2003). The number of different words (NDW) indicates lexical diversity (Muñoz et al., 2003). Mean length of utterance (MLU) is related to stages of syntactic development (Brown, 1973) and reflects grammatical complexity (Scarborough, Rescorla, Tager-Flusberg, Fowler, & Sudhalter, 1991). These measures can be generated by language analysis software, such as the Systematic Analysis of Language Transcript (Miller & Chapman, 2002) and Computerized Language Analysis (MacWhinney, 2000). Compared with fine-grained microstructure measures, these measures provide more general indices of children's linguistic skills.
On the basis of previous literature, we categorized children's narrative skills into three components: macrostructure, general microstructure, and fine-grained microstructure. In the following, we will review findings from Indo-European languages under the three components. Then, we will review findings from Mandarin-speaking children with LI and Cantonese-speaking children with LI. Together, these bodies of literature informed our selection of narrative measures.
Narrative Skills in Indo-European Languages
Macrostructure
Across different Indo-European languages, children with LI have demonstrated lower performance in macrostructure components of story settings, topic maintenance, problem resolution, event sequencing, and internal states (e.g., Miranda, Mccable, & Bliss, 1998; Squires et al., 2014; Tsimpli et al., 2016). The usage of evaluative devices is a particularly vulnerable domain. Children with LI have difficulties using words to express diverse emotions, such as mental states (e.g., happy), attention-seeking exclamations (e.g., look!), and affective behaviors (e.g., He was crying; Reilly et al., 2004). Both the deficits in language and theory of mind (i.e., taking others' perspectives into account) may contribute to the low performance on internal state descriptions in children with LI (de Villiers, 2007). On the one hand, understanding others' intentions and emotions is a prerequisite for expressing internal responses; on the other hand, improvement in language helps children to verbally organize observations of internal responses.
Children with LI do not always perform more poorly on all narrative macrostructure elements. In Norbury and Bishop (2003), no difference was found between the English-speaking, typically developing (TD) group and the group with LI (6 to 10 years old) in the inclusion of initiating events, attempts, and resolutions. While the two groups achieved high scores in initiating events and attempts, resolutions seemed to be challenging for both the TD group and the group with LI. The authors claimed that the ability to include resolutions developed late in both typical and atypical children. However, other later-acquired elements, such as internal responses and plans, may have provided a more complete picture of children's narrative performance (Heilmann, Miller, Nockerts, & Dunaway, 2010). Heilmann et al. also pointed out that a sensitive macrostructure evaluation should measure both quantity and quality (i.e., whether children's production is related to the primary storyline) of macrostructure elements. The examination of both aspects should exhibit better sensitivity because a scoring rubric of this type is more stringent, hence better equipped to identify areas of weaknesses in children's narrative skills.
General Microstructure
General microstructure measures have been extensively studied in previous research. MLU and the usage of complex sentences reflect syntactic complexity (Scarborough et al., 1991), and both have been found to be indicators distinguishing children with and without LI across different languages (e.g., English: Fey et al., 2004; Rice et al., 2010; Greek: Tsimpli et al., 2016; Spanish: Restrepo, 1998). Rice et al. (2010)  found that both MLU in words and MLU in morphemes were reliable indices that identified English-speaking children with LI in a wide age range, from 3 to 9 years old. English-speaking children with LI displayed lower usage of complex sentences (Reilly et al., 2004), which were defined as containing two verb phrases, with one coordinated or subordinated to the other (e.g., The boy WANTS to OPEN the box).
Diversity measures (i.e., NDW) are more likely to reveal language deficits than productivity measures (i.e., TNW and TNU). In English and Greek, children with LI produced fewer NDW than children without LI (Hewitt, Hammer, Yont, & Tomblin, 2005; Rezzonico et al., 2015; Tsimpli et al., 2016). The two productivity measures, TNW and TNU, do not seem to differentiate children with and without LI. Children with LI were as productive as TD age controls in TNW (Guo, Tomblin, & Samelson, 2008; Hick, Joseph, Conti-Ramsden, Serratrice, & Faragher, 2002) and total number of morphemes (Norbury & Bishop, 2003). Similarly, the two groups of children were comparable in TNU (Cleave, Girolametto, Chen, & Johnson, 2010; Fey et al., 2004; Guo et al., 2008; Norbury & Bishop, 2003). Compared with the diversity measure (i.e., NDW), TNW and TNU reflect verbosity. Language deficits may be more likely to manifest in the quality (reflected by diversity measures) than in the quantity (reflected by productivity measures) of language.
Grammaticality has also been frequently studied. In English, children with LI made more grammatical errors than TD controls, such as omitting and misusing verb auxiliaries, determiners, tense markers, and subject–verb agreement (Leonard, 2014a). Reilly et al. (2004)  calculated the ratio of morphological errors to the total number of prepositions from English-speaking children's narrative production. They found a sharp contrast between the TD group and the group with LI in percentages of errors: nearly 50% for the group with LI and less than 10% for the TD group. Fey et al. (2004)  found that English-speaking children with LI produced a lower percentage of grammatical communication-units (C-units) than TD children in oral narrative production. While TD fourth-grade children achieved grammatical accuracy of 84%, the accuracy of children with LI was 75%. In Swedish, a significant difference was also found between TD children and children with LI in the percentage of grammatically correct C-units (Reuterskiöld et al., 2011).
Fine-Grained Microstructure
In recent years, a sizable body of work has included fine-grained microstructure measures in narrative analysis. Justice et al. (2010)  proposed a fine-grained microstructure assessment protocol, including 18 English properties ranging from sentence structure, phrase structure, modifiers, and nouns to verbs. The authors reported good construct validity and criterion-related validity of their assessment protocol in 262 TD English-speaking children. The results suggested that assessing fine-grained microstructure elements was potentially effective in monitoring child language development and detecting children with LI. By adapting the English protocol into Spanish, Gorman et al. (2016)  created a Spanish microstructure assessment protocol. Its usage in 67 preschool children also indicated good construct and concurrent and predictive validity. Reuterskiöld et al. (2011)  compared Swedish-speaking children with and without LI on several fine-grained microstructure elements. Differences were found in the diversity of verbs. However, aside from the handful of studies, fine-grained microstructure measures have not been widely used to evaluate children with LI.
To summarize, in Indo-European languages, macrostructure and general microstructure measures (lexical diversity, syntactic complexity, and grammaticality) can capture the differences between children with LI and without LI, whereas verbosity measures may not. The emerging literature on fine-grained microstructure measures suggest that these measures are potentially differentiating between children with LI and without LI.
Narrative Skills in Mandarin
Mandarin and Indo-European languages are typologically distinct languages. One prominent difference lies in the area of morphosyntax. Indo-European languages typically have richer morphosyntactic transformations, whereas Mandarin lacks these changes. We take the comparison between Mandarin and English as an illustration. While English uses “-s” to mark plurality, Mandarin does not have a similar plural form. A bare noun can be singular or plural according to the context. While English marks subject–verb agreement, Mandarin does not. English sentences should agree in person and in number (e.g., I am, you are, he is), whereas Mandarin does not have similar rules. Given these Mandarin-specific features, we cannot assume that all measures borrowed from Indo-European languages will be differentiating in Mandarin. The likelihood of finding grammatical errors may be smaller in a narrative context in which children have much flexibility in choosing language expressions. In the following, we will review the three Mandarin narrative studies (Cheung, 2009; Tsai & Chang, 2008; Zhang, 2009) and see what differentiating measures have been found in Mandarin.
Zhang (2009)  compared two 4-year-old children with LI and their age matches. Children with LI needed the examiner to ask questions to elicit production and continue storytelling. The group with LI produced fewer macrostructure elements (e.g., actions, settings) and exhibited lower usage of various expressions of internal state than the TD matches. Likewise, Tsai and Chang (2008)  observed deficits in macrostructure in six Mandarin-speaking children with LI at 8 to 9 years old when compared to age matches. In addition, they found that general microstructure measures revealed group differences, including word productivity (i.e., TNW), lexical diversity (i.e., NDW), and syntactic complexity (i.e., MLU; Tsai & Chang, 2008). The two groups demonstrated comparable performance on sentence productivity (i.e., TNU). This is different from findings in many Indo-European language studies that did not find a difference in either productivity measure (TNW and TNU; e.g., Guo et al., 2008; Norbury & Bishop, 2003). These findings from Tsai and Chang (2008)  need to be replicated using a larger sample size. In addition, fine-grained microstructure evaluation examining the usage of specific linguistic properties was not conducted.
Cheung (2009)  focused on general and fine-grained microstructure elements in an 18-month longitudinal study of two 7-year-old Mandarin-speaking children with LI. The children with LI were paired in MLU with two controls who were 2.5-year-olds. Children with LI showed more usage of various complex sentences than their MLU matches. Regarding the two fine-grained microstructure elements (i.e., classifiers and aspect markers), children with LI did not outperform the TD controls who were almost 5 years younger. This suggests that the two microstructure measures are likely to be delayed in Mandarin-speaking children with LI in comparison to TD age matches. In the following, we will describe the two Mandarin features and children's acquisition of the two features.
Mandarin is extremely rich in the use of nominal classifiers. The number of classifiers in Hanyu Liangci Cidian (A Dictionary of Chinese Classifiers) reached 902 (Zhang, 2007). A nominal classifier is obligatory and must appear between a number/demonstrative/quantifier and a noun. The classifier typically indicates the property of the entity the noun is referring to (Erbaugh, 2006; Li & Thompson, 1981). In Example (1), “gen” is inserted between the number (two) and the noun (needle) indicating a thin, slender, and stick-like object.

(1) 两根针

liǎng gēn zhēn

two classifier-gen needle

two needles

Erbaugh (2006)  pointed out that children acquire classifiers slowly as they expand their vocabulary. It takes time for children to sort different semantic categories ingrained in different classifiers. It also takes time for children to learn the arbitrary usage of some classifiers. For children with LI, the process of sorting semantic categories and acquiring arbitrary usage may be longer.
Mandarin uses grammatical morphemes to mark aspect. Instead of showing the absolute time of a situation, aspect markers express different perspectives on the situation (Li & Thompson, 1981). Generally, aspect markers can be categorized into perfective morphemes (–le, –guo) and progressive morphemes (zai–, –zhe) 1   (Klein, Li, & Hendriks, 2000). Perfective morphemes show that an action is completed or a status is formed, whereas progressive morphemes indicate that the action is in progress. See Example (2) for the usage of perfective marker “le” and Example (3) for the usage of progressive marker “zhe.” In Example (2), the action “mai” (buy) is completed from the speaker's viewpoint, whereas in Example (3), the action “chi” (eat) is in progress.

(2) 小女孩买了一个蛋糕。

Xiǎo nǚhaí maǐ le yí gè dàngāo.

Little girl buy perfective-aspect one classifier-ge cake.

The little girl bought a cake.

(3) 小女孩吃着一个蛋糕。

Xiǎo nǚhaí chī zhe yí gè dàngāo.

Little girl eat progressive-aspect one classifier-ge cake.

The little girl is eating a cake.

Aspect markers can be optional, and the omission of aspect markers does not render a sentence ungrammatical in Cantonese (Fletcher, Leonard, Stokes, & Wong, 2005). Similar to Cantonese, Mandarin also allows the optionality of aspect markers. However, in both languages, there are contexts in which aspect markers are preferred if not obligatory (Fletcher et al., 2005; Klein et al., 2000). It is important to note that older Mandarin-speaking children produced more aspect markers to specify perspectives of time in a narrative setting than younger children (Shu, 2004).
Other Potential Indicators of LI in Mandarin
In addition to a narrative analysis, a growing body of literature investigated the acquisition of Mandarin linguistic features using cloze tasks. In this task, children are asked to fill in words or phrases that are missing where the context mandates them to use the target features. In a study by He and Dai (2012), twelve 5-year-old, Mandarin-speaking children with LI were less accurate in using negations than TD age matches. They either did not use any negation form in an obligatory context or used a wrong negative form that was inappropriate in the context. In Zeng, Li, Li, and He (2013), the same group of children with LI displayed less production of “ba” sentences. The “ba” structure is a Mandarin active sentence structure with a noncanonical word order (“agent + ba + patient + action”). The noncanonical word order may cause more difficulty for children with LI. See Example (4) for an example of “ba” structure.

(4) 她把蛋糕吃完了。

Tā bǎ dàngāo chī wán le.

She ba cake eat resultative-finish perfective-aspect.

She finished eating the cake.

Findings from Cantonese-speaking children with LI motivate the investigation of additional fine-grained microstructure elements. The passive structure, also involving a noncanonical word order, challenges Cantonese-speaking children with LI. Compared with TD age matches, children with LI demonstrated lower percentages of full and grammatical passive sentences in contexts encouraging the production of passive structure (Leonard, Wong, Deevy, Stokes, & Fletcher, 2006). Mandarin passive structure is similar to Cantonese passive structure. A passive structure follows the noncanonical word order of “patient + bei + agent + action.” See Example (5) for Mandarin passive structure.

(5) 他被狗追了。

Tā beì gǒu zhuī le.

He bei dog chase perfective-aspect.

He was chased by a dog.

In summary, evidence from previous Mandarin or Cantonese studies suggests that Mandarin-speaking children with LI may demonstrate difficulties in the above six fine-grained microstructure elements, including classifiers, perfective and progressive aspect markers, negation, active “ba” structure, and passive “bei” structure. It should be noted that except for aspect markers, all features are obligatory if children chose to use the corresponding structures. Though aspect markers are optional, they are more likely to be present in language production from more mature Mandarin speakers (Shu, 2004). In addition to the fine-grained microstructure measures, findings of macrostructure and general microstructure deficits in Mandarin-speaking children with LI need to be replicated. Grammaticality has not been investigated in previous studies in Mandarin. The lack of morphosyntactic features in Mandarin leads us to question whether grammaticality can reliably differentiate Mandarin-speaking children with and without LI in a narrative context.
Research Goals and Predictions
In this study, we intended to identify linguistic deficits in Mandarin-speaking children with LI using narrative analysis. We evaluated narrative production in a larger sample of Mandarin-speaking children with LI (n = 18) and their age-matched controls (n = 18). On the basis of a review of narrative evaluation in Indo-European languages and Mandarin/Cantonese, our narrative analyses included three components: macrostructure, general microstructure (i.e., TNU, TNW, NDW, MLU, usage of complex sentences, and grammaticality), and fine-grained microstructure (i.e., classifiers, perfective and progressive aspect markers, negation, “ba” structure, and “bei” structure).
We expected to see weaknesses in Mandarin-speaking children with LI in macrostructure, as previous narrative findings were consistent in showing the deficit (e.g., de Villiers, 2004; Tsai & Chang, 2008). Mandarin-speaking children with LI would also demonstrate lower performance in lexical diversity (i.e., NDW) and syntactic complexity (i.e., MLU and proportion of complex sentences), as shown in previous narrative studies across different languages (e.g., English: Fey et al., 2004; Mandarin: Tsai & Chang, 2008; Cantonese: Klee, Stokes, Wong, Fletcher, & Gavin, 2004; Greek: Tsimpli et al., 2016). Verbosity (i.e., TNU and TNW) would be comparable between children with LI and without LI on the basis of previous literature (e.g., Norbury & Bishop, 2003). Based on our analysis of Mandarin-specific characteristics (the sparsity of morphosyntactic morphemes), grammaticality would also be comparable between the two groups. Informed by existing literature in Mandarin-speaking or Cantonese-speaking children with LI (Cheung, 2009; He & Dai, 2012; Leonard et al., 2006; Zeng et al., 2013; Zhang, 2009), the six fine-grained microstructure elements hold the most promise to differentiate the group with LI and the TD group. We therefore predicted to see differences between the TD group and the group with LI on the six measures.
Method
Participants
Participants in the current study were drawn from a larger sample who participated in the validation study (Liu et al., 2017) of the Diagnostic Receptive and Expressive Assessment of Mandarin (DREAM; Ning, Liu, & de Villiers, 2014). The children were recruited from the Developmental and Behavioral Pediatrics Clinic at Shanghai Children's Medical Center. All families with children between 2;6 (years;months) and 7;11 who visited the hospital during October 2014 were invited to participate. A total of 300 children were initially recruited, but 70 of them were excluded because they did not meet the following criteria: normal hearing, normal or corrected-to-normal vision, and no diagnosis of autism, neurological disorder, genetic disorder, intellectual disability, or cerebral palsy. Children were administered a battery of tests, including but not limited to the DREAM, the Primary Test of Nonverbal Intelligence (PTONI; Ehrler & McGhee, 2008), and either a spontaneous language (for children between 2;6 and 3;11) or a narrative sample (for children between 4;0 and 7;11). Of the 230 children, 99 (age range: 4;0–7;11) produced narratives elicited by the experimental version of the Mandarin Expressive Narrative Test (MENT; de Villiers & Liu, 2014). 2  
We used a set of criteria to qualify children with LI in this study: (a) children had at least one component standard score at or below 80 (1.3 SD below the mean or the 10th percentile) on the DREAM; (b) children had difficulty with oral language according to pediatrician's judgment; and (c) children had a nonverbal IQ score that is 70 (2 SDs below the mean) or above on the PTONI. 3  
The DREAM is a standardized oral language test for children ages 2;6 to 7;11. It was normed on a nationally representative sample of 969 children in Mainland China. The test provides four component scores: receptive language, expressive language, syntax, and semantics. As reported by Liu et al. (2017), test–retest reliability was high (r = .85). External validity was assessed using spontaneous language indices (e.g., sentence complexity, vocabulary diversity) and narrative indices (e.g., the inclusion of mental verbs and connectives). 4   The correlation coefficient between DREAM scores and spontaneous language was .7 (p < .001) and that between DREAM and narrative indices was .45 (p < .01).
We used a cutoff score of 80 on any of the DREAM components as one of our inclusionary criteria. According to Liu et al. (2017), the DREAM demonstrated the best sensitivity (73%) and specificity (82%) using this criterion (< 80 on one component) when measured against a priori judgment by pediatricians, who usually make decisions of this kind in China. The sensitivity of the DREAM improved to 95% when spontaneous language sample (either spontaneous or narrative) performance and a priori judgment were combined as the gold standard. Specificity remained the same under the second approach.
Multiple researchers have advocated for the inclusion of ecologically valid indicators of LI in addition to a statistically driven definition. Bishop (1997)  suggested the use of a real-life concern expressed by those who are familiar with the child. Bedore, Peña, Joyner, and Macken (2011)  and Peña, Resendiz, and Gillam (2007)  reported that parent, teacher, and clinician judgments provided reliable indicators of language ability. In light of these recommendations, we used the judgment of a developmental and behavioral pediatrician as a converging indicator of LI. Upon enrollment in the study, the caregiver of each child was asked if they had any concerns about the child's oral language ability. If the answer was affirmative, the pediatrician asked follow-up questions in an informal interview (e.g., the child's ability to ask and answer questions and understand and follow directions, vocabulary, word retrieval, sentence formulation skills, and conservational and peer interaction skills). Based on the caregivers' answers, the pediatrician formed a clinical impression.
For this study, the 18 children (age range: 4;3–7;11) met all three criteria and were categorized as having LI. For each child in the group with LI, we selected a TD child who was within 5 months of age as a match (age range: 4;3–7;9). The TD controls achieved 80 or higher on all four components of the DREAM, and there were no caregiver concerns regarding language development. Children with LI achieved lower performance than the TD children in the four components and the total scores of the DREAM (see Table 1). Children with LI in our sample more commonly displayed deficits in expressive language (17/18) and in the domain of syntax (10/18). 5  
Table 1. Participant information by typicality.
Participant information by typicality.×
Measure LI (n = 18)
TD (n = 18)
t p value
M SD M SD
Age (months;years) 6;2 1;2 6;2 1;1 0.14 .894
Gender: male/female 14/4 10/8
Education 2.33 1.14 3.00 1.28 1.65 .108
IQ 90.44 16.69 98.89 12.31 1.73 .094
DREAM–Total 83.61 9.77 100.61 8.47 5.85 <.001
DREAM–Receptive 84.65 10.57 100.72 9.08 4.53 <.001
DREAM–Expressive 72.44 7.64 98.89 9.88 7.79 <.001
DREAM–Syntax 79.33 7.67 94.06 6.70 6.08 <.001
DREAM–Semantics 87.50 13.00 106.89 11.85 4.99 <.001
Note. Education is presented in scales ranging from 1 to 5: 5 = PhD/master's degree, 4 = bachelor's degree, 3 = associate degree, 2 = high school, 1 = middle school or lower. The IQ scores and DREAM scores are standard scores. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; DREAM = Diagnostic Receptive and Expressive Assessment of Mandarin.
Note. Education is presented in scales ranging from 1 to 5: 5 = PhD/master's degree, 4 = bachelor's degree, 3 = associate degree, 2 = high school, 1 = middle school or lower. The IQ scores and DREAM scores are standard scores. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; DREAM = Diagnostic Receptive and Expressive Assessment of Mandarin.×
Table 1. Participant information by typicality.
Participant information by typicality.×
Measure LI (n = 18)
TD (n = 18)
t p value
M SD M SD
Age (months;years) 6;2 1;2 6;2 1;1 0.14 .894
Gender: male/female 14/4 10/8
Education 2.33 1.14 3.00 1.28 1.65 .108
IQ 90.44 16.69 98.89 12.31 1.73 .094
DREAM–Total 83.61 9.77 100.61 8.47 5.85 <.001
DREAM–Receptive 84.65 10.57 100.72 9.08 4.53 <.001
DREAM–Expressive 72.44 7.64 98.89 9.88 7.79 <.001
DREAM–Syntax 79.33 7.67 94.06 6.70 6.08 <.001
DREAM–Semantics 87.50 13.00 106.89 11.85 4.99 <.001
Note. Education is presented in scales ranging from 1 to 5: 5 = PhD/master's degree, 4 = bachelor's degree, 3 = associate degree, 2 = high school, 1 = middle school or lower. The IQ scores and DREAM scores are standard scores. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; DREAM = Diagnostic Receptive and Expressive Assessment of Mandarin.
Note. Education is presented in scales ranging from 1 to 5: 5 = PhD/master's degree, 4 = bachelor's degree, 3 = associate degree, 2 = high school, 1 = middle school or lower. The IQ scores and DREAM scores are standard scores. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; DREAM = Diagnostic Receptive and Expressive Assessment of Mandarin.×
×
In addition to age, we made an effort to match the group with LI and the TD group on primary caregivers' education and children's nonverbal IQ scores. Education was ranked into five levels ranging from 1 to 5. Five represented the highest education level (PhD/master's), and 1 represented the lowest (middle school or lower). Nonverbal IQ was measured using the Chinese translation of the PTONI (Ehrler & McGhee, 2008). The test included a set of pictures for each testing item, and children were required to point to a picture that was different from the others. The PTONI was normed in a culturally diverse sample, with 1,010 children from 38 states in the United States. Though it was not normed in Mainland China, it was considered to be largely free of cultural bias. The group differences in caregiver education and PTONI scores were not significant. Though not significant, the p levels were close to .10. To address these potential confounds, we examined the correlations between dependent variables and education level/IQ scores before conducting group comparisons. If they were significantly correlated, we would enter them as covariates.
Materials and Procedure
Three stories were depicted on three wordless picture series from the experimental version of the MENT. Each story had at least two characters, a complication in the events that encouraged talk of problems and resolutions, visual presentation of characters' emotions, and depiction of multiple actions. For example, one story contained two characters. One character sees some food placed in one location and leaves. The other character moves the food to a new place out of sight and leaves. When the first character returns, he or she tries to look for the food. Thought balloons were depicted to demonstrate characters' desires and thoughts and to elicit production of internal responses and plans. For instance, when the first character decides to move the food, a balloon shows that the move is meant to keep the food fresh. When the other character comes back, there is a thought balloon showing that he or she is thinking of the food. In order to tell this story, children need to take the characters' perspective into account and describe their internal states. Detailed information about the MENT can be found in Appendix C of Liu et al. (2017) .
An examiner presented pictures to the children one by one in sequence. After viewing all pictures, the examiner asked the children to tell the story with pictorial support. If a child did not follow the sequence in which the pictures were presented, the examiner corrected the child and required the child to follow the sequence. All stories were video-recorded. A linguistics undergraduate who is a native Mandarin speaker transcribed the recordings into Chinese characters. The undergraduate was not aware of the LI/TD status of the participants. The first author, also a native Mandarin speaker, proofread all transcriptions and corrected transcription errors. The first author then coded the samples using the Computerized Language Analysis software program (MacWhinney, 2000). At the time of coding, the first author was also blind to the group membership.
Coding
Macrostructure
On the basis of Monitoring Indicators of Scholarly Language (Gillam et al., 2017), we coded seven macrostructure elements, including character, setting, initiating event, internal response, plan, action series, and consequence. Each element was scored on a scale from 0 to 3. As in the Monitoring Indicators of Scholarly Language, we used a combination of quantitative and qualitative analyses. We took into account the frequency of occurrence of each macrostructure element, as well as the connection of the production to the main storyline. For example, for the element action series, 0 means that no action is taken by any character, 1 is including actions that are taken by characters but not related to the story, 2 is including at least a series of actions that is related to the main story but does not form a complete episode, and 3 means that the action series relates to the main story and forms a complete episode. Table 2 presents macrostructure scoring rubric and examples.
Table 2. Macrostructure scoring rubric and examples.
Macrostructure scoring rubric and examples.×
Macrostructure elements Score
0 1 2 3
Character No character is included or only pronouns are used.
e.g., he, she
Includes characters that are not related to the storyline. Includes one of the two characters. Includes both characters.
e.g., girl, mother
Setting No time or place is stated. Includes at least one time or place that is not related to the storyline. Includes one time or one place that is related to the storyline.
e.g., 1 day, in the fridge
Includes at least two times or two places that are related to the storyline.
Initiating event (IE) A problem or starting event is not stated. Includes events or problems that are not related to the storyline. Includes one event or problem that is related to the primary storyline. e.g., The girl wants to eat it. Includes more than one event or problem that is related to the primary storyline.
Internal response No feelings, desires, or thoughts are stated. Includes expressions of feelings, desires, or thoughts that are not related to the IEs. Includes two feelings, desires, or thoughts that are directly related to the IEs.e.g., The mother thought that it should be put into fridge. Includes more than two feelings, desires, or thoughts that are directly related to the IEs.
Plan No statement is provided about the character's plan to solve the problem. Includes one statement of plan that is not related to the IEs. Includes one statement of plan that is directly related to the IEs.
e.g., She is going to eat it.
Includes at least two statements of plan that are directly related to the IEs.
Action series No action is taken by any of the characters. There are a series of random descriptions.
e.g., A girl. Another girl.
Actions are taken by the characters but are not directly related to the IEs.
e.g., They are boiling eggs. (no such action depicted)
At least one action that is directly related to the IEs is taken by the main character. However, the action series do not form a complete episode. e.g., She gets the cake. Includes a series of actions that are directly related to the IEs and can be formed into a complete episode.
e.g., She is afraid the cake may melt. She gets the cake and moves it into the fridge.
Consequences No consequence is stated. There are statements of consequences, but they are not related to the IEs. Includes one consequence that is directly related to the IEs.
e.g., She puts the cake into the fridge.
Includes at least two consequences that are directly related to the IEs.
Note. The examples are from one of the three stories. The rubric varies for different stories on the basis of the storyline and observations of children's overall performance.
Note. The examples are from one of the three stories. The rubric varies for different stories on the basis of the storyline and observations of children's overall performance.×
Table 2. Macrostructure scoring rubric and examples.
Macrostructure scoring rubric and examples.×
Macrostructure elements Score
0 1 2 3
Character No character is included or only pronouns are used.
e.g., he, she
Includes characters that are not related to the storyline. Includes one of the two characters. Includes both characters.
e.g., girl, mother
Setting No time or place is stated. Includes at least one time or place that is not related to the storyline. Includes one time or one place that is related to the storyline.
e.g., 1 day, in the fridge
Includes at least two times or two places that are related to the storyline.
Initiating event (IE) A problem or starting event is not stated. Includes events or problems that are not related to the storyline. Includes one event or problem that is related to the primary storyline. e.g., The girl wants to eat it. Includes more than one event or problem that is related to the primary storyline.
Internal response No feelings, desires, or thoughts are stated. Includes expressions of feelings, desires, or thoughts that are not related to the IEs. Includes two feelings, desires, or thoughts that are directly related to the IEs.e.g., The mother thought that it should be put into fridge. Includes more than two feelings, desires, or thoughts that are directly related to the IEs.
Plan No statement is provided about the character's plan to solve the problem. Includes one statement of plan that is not related to the IEs. Includes one statement of plan that is directly related to the IEs.
e.g., She is going to eat it.
Includes at least two statements of plan that are directly related to the IEs.
Action series No action is taken by any of the characters. There are a series of random descriptions.
e.g., A girl. Another girl.
Actions are taken by the characters but are not directly related to the IEs.
e.g., They are boiling eggs. (no such action depicted)
At least one action that is directly related to the IEs is taken by the main character. However, the action series do not form a complete episode. e.g., She gets the cake. Includes a series of actions that are directly related to the IEs and can be formed into a complete episode.
e.g., She is afraid the cake may melt. She gets the cake and moves it into the fridge.
Consequences No consequence is stated. There are statements of consequences, but they are not related to the IEs. Includes one consequence that is directly related to the IEs.
e.g., She puts the cake into the fridge.
Includes at least two consequences that are directly related to the IEs.
Note. The examples are from one of the three stories. The rubric varies for different stories on the basis of the storyline and observations of children's overall performance.
Note. The examples are from one of the three stories. The rubric varies for different stories on the basis of the storyline and observations of children's overall performance.×
×
General Microstructure Measures
We segmented sentences on the basis of C-unit (Loban, 1976) that consists of a main clause with all dependent clauses attached to it. For example, “The little boy said ‘I don't know’” is a C-unit. It has a subordinate clause “I don't know” embedded in the main clause “The little boy said.” “He found a ladder. He went there.” consists of two C-units and should be counted as two utterances. The second sentence does not attach to the first, so both are independent clauses. Sentence segmentation formed the basis of the TNU measure. Word segmentation was at the word level instead of the morpheme level, due to the fact that Mandarin grammatical features are realized at the word level. Word segmentation formed the basis of the TNW and NDW measures.
We coded complex sentences (C-units) and calculated percentages of complex sentences (number of complex sentences divided by TNU). A sentence with two or more than two main verbs was regarded as a complex sentence. Two verbs can have an embedding relation in which one clause is embedded in another clause. In Example (6), the clause with the verb “zou” (walked away/left) is embedded in the clause with the verb “kan” (see). Two verbs can also have a compounding relation. In Example (7), “huishou” (wave) and “shuo” (say) are compounded showing a sequence of actions. This structure is a serial verb construction (no connective between the two verbs; Cheung, 2009).

(6) 他看到男孩走了。

Tā kàn dào nánhaí zǒu le.

He see verb-resultative boy leave perfective-marker

He saw that the boy left.

(7) 他挥手说再见。

Tā huī shǒu shuō zaìjiàn.

He wave hand say goodbye

He waved and said goodbye.

In addition, we coded ungrammatical sentences (C-units) in which ungrammaticality could arise from any component of a sentence. Example (8) includes a locative phrase in which the preposition is missing. In addition, the sentence has an incomplete noun phrase in which the head noun is missing. We calculated percentages of ungrammaticality (number of ungrammatical sentences divided by TNU).

(8) 爸爸说要(在)屋顶上画一个红色(?)。

Bàba shuō yào (zaì) wū dǐng shàng huà yí gè hóngsè (?)

Father say need (preposition “zai” missing) house roof above paint one classifier red (?).

Father said that (they) need to paint a red (?) (on) the roof of the house.

Fine-Grained Microstructure Measures
Based upon a review of Mandarin grammar (Li & Thompson, 1981) and studies of Mandarin or Cantonese microstructure and grammar acquisition (Cheung, 2009; He & Dai, 2012; Leonard et al., 2006; Zeng et al., 2013; Zhang, 2009), we counted the frequency of the “ba” structure, “bei” structure, negation, classifier, perfective aspect marker “le/guo,” and progressive aspect marker “zai/zhe.” All coded occurrences were accurate usage of these features (inaccurate usage was included in the measure of grammaticality above). See Table 3 for descriptions and examples of each element.
Table 3. Fine-grained microstructure definitions and examples.
Fine-grained microstructure definitions and examples.×
Fine-grained microstructure elements Definitions Examples
Ba Mandarin active sentence structure with a word order “agent + ba + patient + action” (“ba” is obligatory) 弟弟屋顶涂成黄色。
Dìdi bǎ wūding tú chéng huángsè.
Brother ba roof paint resultative yellow.
The younger brother painted the roof yellow.
Bei Mandarin passive sentence structure with a word order “patient + bei + agent + action” (“bei” is obligatory) 梯子他的爸爸拿走了。
Tīzi beì tā de bàba ná zǒu le.
Ladder bei he possessive-particle father carry go-resultative perfective-marker.
The ladder was taken away by his dad.
Negation A negation word negating a word or a sentence (negation words are obligatory) 这个小女孩睡觉。
Zhè gè xiǎo nǚhaí bú shuìjiào.
This classifier little girl no sleep.
This little girl is not sleeping.
Classifier A word in between a number and a noun showing the property of the noun (the generic classifier “ge” was not counted; classifiers are obligatory) 小妹妹搬来了一椅子。
Xiǎo meìmei bān laí le yì ba yǐzi.
Little sister move come-resultative perfective-aspect one classifier chair.
The younger sister brought one chair.
Perfective aspect marker Mandarin perfective aspect “le”/“guo” marker after either a verb or an adjective showing an action or status is completed (perfective aspect markers are optional in some cases) 医生来
Yīshēng laí le.
Doctor come perfective-maker.
The doctor came.
弟弟高
Dìdi gāo le.
Brother tall perfective-marker.
The younger brother became taller.
Progressive aspect marker Mandarin progressive aspect marker “zai/zhe” showing an action is progressing (progressive aspect markers are optional in some cases) 小华刷墙。
Xiǎohuá zaì shuā qiáng.
Xiaohua progressive-marker brush wall.
Xiaohua is painting the wall.
Table 3. Fine-grained microstructure definitions and examples.
Fine-grained microstructure definitions and examples.×
Fine-grained microstructure elements Definitions Examples
Ba Mandarin active sentence structure with a word order “agent + ba + patient + action” (“ba” is obligatory) 弟弟屋顶涂成黄色。
Dìdi bǎ wūding tú chéng huángsè.
Brother ba roof paint resultative yellow.
The younger brother painted the roof yellow.
Bei Mandarin passive sentence structure with a word order “patient + bei + agent + action” (“bei” is obligatory) 梯子他的爸爸拿走了。
Tīzi beì tā de bàba ná zǒu le.
Ladder bei he possessive-particle father carry go-resultative perfective-marker.
The ladder was taken away by his dad.
Negation A negation word negating a word or a sentence (negation words are obligatory) 这个小女孩睡觉。
Zhè gè xiǎo nǚhaí bú shuìjiào.
This classifier little girl no sleep.
This little girl is not sleeping.
Classifier A word in between a number and a noun showing the property of the noun (the generic classifier “ge” was not counted; classifiers are obligatory) 小妹妹搬来了一椅子。
Xiǎo meìmei bān laí le yì ba yǐzi.
Little sister move come-resultative perfective-aspect one classifier chair.
The younger sister brought one chair.
Perfective aspect marker Mandarin perfective aspect “le”/“guo” marker after either a verb or an adjective showing an action or status is completed (perfective aspect markers are optional in some cases) 医生来
Yīshēng laí le.
Doctor come perfective-maker.
The doctor came.
弟弟高
Dìdi gāo le.
Brother tall perfective-marker.
The younger brother became taller.
Progressive aspect marker Mandarin progressive aspect marker “zai/zhe” showing an action is progressing (progressive aspect markers are optional in some cases) 小华刷墙。
Xiǎohuá zaì shuā qiáng.
Xiaohua progressive-marker brush wall.
Xiaohua is painting the wall.
×
Reliability
Following the same rubric, another research assistant independently transcribed 20% of the narrative production that were randomly selected from all narratives. Regarding macrostructure, Cohen's k (a statistic measuring interrater agreement for qualitative data) indicated that agreement between the two coders was substantial (k = 0.633, p < .0001; Landis & Koch, 1977). Sentence and word segmentation formed the basis for the general microstructure measures of MLU, NDW, TNW, and TNU. Following Rezzonico et al. (2015), reliability of sentence and word segmentation was computed using the formula: number of agreements / (number of agreements + number of disagreements). The reliability was 89% for sentence segmentations (total: 263, agreement: 234, disagreement: 29) and 93% for word segmentations (total: 1,719, agreement: 1,605, disagreement: 114). All disagreements were resolved by discussion. For the other two general microstructure elements (i.e., complex sentences, ungrammatical sentences) and the six fine-grained microstructure elements, we followed Justice et al. (2010) : Agreement occurred when two coders scored within one occurrence difference. For example, if one rater counted the occurrence of an element four times and the other counted it five times, their scorings were considered consistent. The interrater consistency for these measures ranged from 91% to 100%.
Results
We first conducted Pearson's correlations to see whether education level and IQ scores were related to the dependent variables. No significant correlations were found between education levels/IQ scores and any of the dependent variables. Therefore, we did not enter education level and IQ scores as covariates.
In the following, we conducted 18 group comparisons (all measures except proportions of complex sentences and ungrammatical sentences) using independent-samples t tests. To protect against the inflation of Type I error rate, a Benjamini–Hochberg procedure (Benjamini & Hochberg, 1995) was conducted for the 18 comparisons. The Benjamini–Hochberg procedure is less conservative than the Bonferroni correction that may mask important clinical findings by increasing Type II error (false negative; Glickman, Rao, & Schultz, 2014; Perneger, 1998). This procedure controls the false discovery rate (d), the expected proportion of errors among all the rejected hypotheses, by ordering p values from smallest to largest. In the Benjamini–Hochberg procedure, smaller p values are retained based on the number of comparisons. If a p value is equal or less than d × (i/n) (i is the rank of the p values, and n is the number of comparisons), the test is significant. We set the false discovery rate at 0.05, a cutoff often used (Glickman et al., 2014). At a false discovery rate of 0.05, a difference was significant at p < .025. We also calculated Cohen's d effect size (mean differences between the two groups divided by pooled standard deviations) to reveal clinically important discoveries. A Cohen's d value of 0.8 is considered a large effect; 0.5, a medium effect; and 0.2 a small effect (Cohen, 1988).
Independent-samples t tests may not be appropriate for percentage comparisons. For proportions of complex sentences (number of complex sentences divided by TNU) and ungrammatical sentences (number of ungrammatical sentences divided by TNU), we used generalized linear models with a binomial family and log link that compared the two groups on the likelihood of using complex sentences and ungrammatical sentences. In the models, odds ratios were used to report effect estimates. The Benjamini–Hochberg procedure was also implemented to reduce Type I error for the two comparisons, and the false discovery rate was also set at 0.05.
Macrostructure
Independent-samples t tests were used to compare the two groups on macrostructure elements. Table 4 presents the results. The two groups significantly differed on macrostructure total scores. Regarding individual elements, the group with LI displayed lower performance than the TD group on character, setting, internal response, action series, and consequence. Large effect sizes for the above differences by group were found. Particularly, children with LI displayed very little usage of internal responses, and the averaged score of 0.07 indicated that there were almost no statements about characters' internal states. No significant difference was found for the element of plan, with both groups showing very little production of the plan (both groups' averaged scores were below 0.5). Between-groups difference on initiating event approached significance with a medium effect size.
Table 4. Comparisons of macrostructure between the group with LI and the TD group.
Comparisons of macrostructure between the group with LI and the TD group.×
Macrostructure elements LI
TD
t p value Cohen's d
M SD M SD
Character 1.55 1.17 2.52 0.54 3.20 .004 a 1.065
Setting 1.87 0.79 2.43 0.57 2.42 .022 a 0.813
Initiating event 2.03 0.84 2.46 0.51 1.88 .071 0.619
Internal response 0.07 0.18 0.76 0.62 4.46 < .001 a 1.511
Plan 0.37 0.56 0.46 0.44 0.55 .588 0.177
Action series 2.02 0.46 2.52 0.46 3.24 .003 a 1.087
Consequence 1.25 0.96 1.98 0.74 2.56 .015 a 0.852
Total 9.16 3.80 13.13 2.46 3.73 .001 a 1.240
Note. All scores were averages of the three stories. All elements were scaled from 0 to 3. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.
Note. All scores were averages of the three stories. All elements were scaled from 0 to 3. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.×
a Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.
Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.×
Table 4. Comparisons of macrostructure between the group with LI and the TD group.
Comparisons of macrostructure between the group with LI and the TD group.×
Macrostructure elements LI
TD
t p value Cohen's d
M SD M SD
Character 1.55 1.17 2.52 0.54 3.20 .004 a 1.065
Setting 1.87 0.79 2.43 0.57 2.42 .022 a 0.813
Initiating event 2.03 0.84 2.46 0.51 1.88 .071 0.619
Internal response 0.07 0.18 0.76 0.62 4.46 < .001 a 1.511
Plan 0.37 0.56 0.46 0.44 0.55 .588 0.177
Action series 2.02 0.46 2.52 0.46 3.24 .003 a 1.087
Consequence 1.25 0.96 1.98 0.74 2.56 .015 a 0.852
Total 9.16 3.80 13.13 2.46 3.73 .001 a 1.240
Note. All scores were averages of the three stories. All elements were scaled from 0 to 3. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.
Note. All scores were averages of the three stories. All elements were scaled from 0 to 3. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.×
a Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.
Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.×
×
General Microstructure Measures
We compared children's performance on general microstructure measures, including MLU, NDW, TNW, and TNU. MLU was calculated using the formula: MLU = TNW/TNU. Independent-samples t tests were conducted to compare the group with LI and the TD group on these measures (see Table 5). Children with LI demonstrated shorter MLU and produced fewer NDW than their TD peers with large effect sizes. The two groups did not differ on TNW and TNU, with small to medium effect sizes. It should be noted that both groups produced relatively short stories (TNU: the group with LI ranged between three and 26 utterances per story; the TD group ranged between eight and 21 utterances per story), indicating a limited amount of data in the narrative samples.
Table 5. Comparisons of general microstructure between the group with LI and the TD group.
Comparisons of general microstructure between the group with LI and the TD group.×
General microstructure elements LI
TD
t p value Cohen's d
M SD M SD
MLU 6.18 1.85 7.52 1.36 2.46 .019 a 0.825
NDW 35.19 16.43 47.57 13.22 2.49 .018 a 0.830
TNW 71.38 49.53 93.48 28.79 1.64 .111 0.546
TNU 11.45 5.24 12.70 3.42 0.85 .402 0.283
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; MLU = mean length of utterance; NDW = number of different words; TNW = total number of words; TNU = total number of utterances.
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; MLU = mean length of utterance; NDW = number of different words; TNW = total number of words; TNU = total number of utterances.×
a Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.
Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.×
Table 5. Comparisons of general microstructure between the group with LI and the TD group.
Comparisons of general microstructure between the group with LI and the TD group.×
General microstructure elements LI
TD
t p value Cohen's d
M SD M SD
MLU 6.18 1.85 7.52 1.36 2.46 .019 a 0.825
NDW 35.19 16.43 47.57 13.22 2.49 .018 a 0.830
TNW 71.38 49.53 93.48 28.79 1.64 .111 0.546
TNU 11.45 5.24 12.70 3.42 0.85 .402 0.283
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; MLU = mean length of utterance; NDW = number of different words; TNW = total number of words; TNU = total number of utterances.
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; MLU = mean length of utterance; NDW = number of different words; TNW = total number of words; TNU = total number of utterances.×
a Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.
Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.×
×
We used generalized linear models to compare the usage of complex sentences and ungrammatical sentences between the two groups. In the models, dependent variables are binary (e.g., 0 indicates that a sentence is grammatical and 1 indicates that a sentence is ungrammatical). The fixed effect was the group, and participants were treated as a random effect. The group had an effect on the usage of complex sentences, F(1, 1244) = 20.25, p < .0001, odds ratio = 0.55. The odds ratio indicated that the group with LI was 45% less likely to produce complex sentences than the TD group. On average, 38% (SD = 9%) of the sentences produced by TD children were complex sentences, and 24% (SD = 16%) of the sentences produced by children with LI were complex sentences. No group difference was found for the usage of ungrammatical sentences, F(1, 1244) = 0.708, p = .400, odds ratio = 1.12. The odds ratio of 1.12 indicated that children with LI were 12% more likely than TD children to produce ungrammatical sentences. Both groups produced very few ungrammatical sentences. On average, 2% (SD = 3%) of the sentences produced by TD children were ungrammatical sentences, and 4% (SD = 4%) of the sentences produced by children with LI were ungrammatical sentences. Significance remained the same after the Benjamini–Hochberg procedure.
Fine-Grained Microstructure Measures
Independent-samples t tests were also used to compare fine-grained microstructure elements. See Table 6 for comparison results. The group with LI displayed lower production of Mandarin perfective aspect markers with a large effect size. Though the differences between the two groups on the “bei” structure and classifier were not significant after the Benjamini–Hochberg correction, the effect size of the “bei” structure was large, and the effect size of “classifier” approached large. Therefore, we considered the differences to be of clinical significance. 6   Children with LI did not show any accurate usage of Mandarin passive “bei” structure. They also displayed very low usage of classifiers. Otherwise, all children, with LI or TD, produced some instances of all examined microstructure elements.
Table 6. Comparisons of fine-grained microstructure between the group with LI and the TD group.
Comparisons of fine-grained microstructure between the group with LI and the TD group.×
Fine-grained microstructure elements LI
TD
t p value Cohen's d
M SD M SD
Ba structure 0.83 1.03 1.04 0.68 0.70 .490 0.240
Bei structure 0.00 0.00 0.13 0.23 2.36 .030 0.810
Negation 1.01 0.66 1.20 0.85 0.73 .472 0.250
Classifier 0.03 0.12 0.37 0.63 2.25 .037 0.750
Perfective aspect marker 2.56 2.11 4.57 1.31 3.45 .002 a 1.145
Progressive aspect marker 0.89 1.11 0.87 0.76 −0.09 .927 −0.021
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.×
a Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.
Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.×
Table 6. Comparisons of fine-grained microstructure between the group with LI and the TD group.
Comparisons of fine-grained microstructure between the group with LI and the TD group.×
Fine-grained microstructure elements LI
TD
t p value Cohen's d
M SD M SD
Ba structure 0.83 1.03 1.04 0.68 0.70 .490 0.240
Bei structure 0.00 0.00 0.13 0.23 2.36 .030 0.810
Negation 1.01 0.66 1.20 0.85 0.73 .472 0.250
Classifier 0.03 0.12 0.37 0.63 2.25 .037 0.750
Perfective aspect marker 2.56 2.11 4.57 1.31 3.45 .002 a 1.145
Progressive aspect marker 0.89 1.11 0.87 0.76 −0.09 .927 −0.021
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.×
a Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.
Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.×
×
Discussion
This study compared narrative skills between Mandarin-speaking children with LI and their age-matched TD controls. Based on previous narrative studies in children with LI, comparisons were conducted in three components: macrostructure, general microstructure, and fine-grained microstructure. For macrostructure, differences between the two groups existed in the descriptions of characters, settings, internal responses, complete action series, and consequences. Regarding general microstructure, the group with LI demonstrated shorter MLU, lower NDW, and lower usage of complex sentences than the TD group. For fine-grained microstructure, children with LI showed lower usage of passive “bei” structure, classifiers, and perfective aspect markers. Group difference on these measures displayed close to large to very large effect sizes (Cohen's d ranged from 0.75 for classifiers to 1.51 for internal response).
Macrostructure measures were sensitive to the presence of LI in Mandarin, as indicated by macrostructure total scores and performance on five of the seven individual macrostructure elements. This is consistent with previous narrative findings in LI (Miranda et al., 1998; Reilly et al., 2004; Tsai & Chang, 2008; Zhang, 2009). In our study, the macrostructure element plan was rarely used by children, both with LI and TD, the oldest of whom were almost 8 years old. This suggests that the plan is a higher level macrostructure element acquired late by children. As we discussed in the beginning, macrostructure assessment should include later-acquired elements so that the assessment is sufficiently challenging and can cover a wider age range. Future investigations of macrostructure may include the assessment of the plan for children in later elementary grades. It is possible that the plan will surface as an element of deficit for children with LI in higher grade levels.
We found that among other things, Mandarin-speaking children with LI showed significant deficits in the production of internal responses. Their production of internal response elements was close to floor. In Mandarin-speaking children with LI, it is likely that the poor performance in internal responses resulted from impairment in both language and theory of mind (de Villiers, 2007). Group differences in the element of initiating event did not reach statistical significance (p = .07). However, the medium effect size (d = 0.62) suggests that children with LI may still need some enhancement in this macrostructure element. Future research is also needed to see if the production of initiating event in narratives is indeed relatively intact in children with LI.
While Mandarin syntactic complexity (i.e., MLU and usage of complex sentences) and lexical diversity (i.e., NDW) were sensitive to the presence of LI, productivity measures (i.e., TNU and TNW) were not. These are consistent with findings from previous studies in many Indo-European languages (e.g., Guo et al., 2008; Hewitt et al., 2005). These findings may suggest that differences between children with and without LI mainly lie in linguistic sophistication of narrative production, not verbosity. Even though children with LI produced a similar number of sentences and words as their TD peers, their production included less-complex sentences and less-diverse vocabulary. We did not replicate Tsai and Chang (2008), in which TNW was different between Mandarin-speaking children with and without LI in a very small sample size.
While grammaticality is very sensitive to the presence of LI in languages with richer morphology (e.g., Reilly et al., 2004), Mandarin-speaking children with LI did not produce more ungrammatical sentences than their TD peers in a narrative setting. The low percentages (4% for LI and 2% for TD) of ungrammatical sentences are in sharp contrast to Fey et al. (2004), wherein up to 16% of the utterances produced by TD fourth graders were ungrammatical. Since Mandarin lacks morphosyntactic features, grammatical errors are less likely to be manifested in Mandarin compared with languages with richer morphosyntactic features. In addition to the lack of complex conjugation systems, Mandarin allows the omission of aspect marking (e.g., perfective aspect “le/guo,” progressive aspect “zai/zhe”). The optionality in aspect marking may also contribute to better grammaticality performance in Mandarin-speaking children with LI than children with LI who speak Indo-European languages.
It should be noted that even though aspect markers can be omitted in Mandarin, more-mature language learners tend to use aspect markers to be clear about perspectives of time in narratives (Shu, 2004). Therefore, the lower usage of perfective aspect markers reflects true deficits in Mandarin-speaking children with LI. It should also be noted that other fine-grained Mandarin linguistic features examined in the current study are not optional. In the “ba” or “bei” structure, the word ba or bei must be included (Li & Thompson, 1981). Similarly, when describing the quantity of an object, classifiers must be present between the number and the noun (Erbaugh, 2006; Li & Thompson, 1981). Thus, the differences between the two groups on the usage of the “bei” structure and classifiers are not confounded by optionality but reflect real differences in children's deployment of these linguistic features.
Another potential reason for low ungrammaticality resides in the spontaneous language sampling context. The narrative context gives children the flexibility to choose expressions that they have already mastered and to avoid expressions that they are not confident with. Differences in grammaticality between children with and without LI may become more prominent in an obligatory context where children are required to use certain language features. Also, this may explain why we did not find a difference by group on negation and “ba” structure, whereas Zeng et al. (2013)  and He and Dai (2012)  found a difference using cloze tasks. However, we think that the influence of context is secondary compared to the impact of language typology. In a narrative context, performance on grammaticality differed significantly between the TD group and the group with LI in many Indo-European languages (e.g., Reilly et al., 2004; Reuterskiöld et al., 2011). For these languages, the flexibility afforded by the spontaneous language context cannot mask the deficits of the group with LI in the marking of verb or noun-related morphological features.
The three fine-grained microstructure elements (i.e., Mandarin passive “bei structure, Mandarin perfective marker “le/guo” and classifiers) are Mandarin-specific features not shared with Indo-European languages. These results resonate with Leonard's (2014b)  proposal that the particular language determines domains of ease and difficulty in children with LI. English-speaking children with LI show particular deficits in English verb conjugations (e.g., tense markers and subject–verb agreement; Leonard, 2014a). Children with LI who speak Italian and Spanish are found to be more likely to demonstrate deficits in noun-related morphology (e.g., clitics, plural inflection; Bedore & Leonard, 2001; Leonard & Dispaldro, 2013). Mandarin-speaking children with LI, however, show a diffuse array of deficits ranging from sentence structure to verb particles and noun modifiers.
Mandarin classifiers are known to be later acquired as a result of their vast number and complex usage (Erbaugh, 2006). Mandarin-speaking children with LI may need extended time learning these forms and their corresponding semantic categories. Regarding passive structure, children generally exhibit late mastery across a number of languages (Leonard et al., 2006; Perovic, Vuksanović, Petrović, & Avramović-Ilić, 2014). Mastery of the passive structures may require more-sophisticated linguistic knowledge and cognitive ability because the forms involve noncanonical word order and are used in special circumstances.
Differences in perfective aspect markers were associated with a very large effect size (d = 1.15). It is possible that children with LI may opt to omit aspect markers when they are not sure of the correct use. However, the lower frequency of perfective marker in the children with LI cannot be fully attributed to the optionality of this grammatical feature because even after we factored out the potential influence of TNW, the difference was still highly significant (p = .006). These uncertainties notwithstanding, we can confidently say that the TD children used perfective aspect marking more frequently, indicating better mastery and clear evidence of perspective taking in various contexts.
Conclusion, Clinical Implications, Limitations, and Future Directions
To conclude, this study compared narrative skills between Mandarin-speaking children with and without LI on macrostructure and microstructure (general and fine-grained) measures. Results revealed that Mandarin-speaking children with and without LI showed comparable performance in productivity and grammaticality in a narrative context. These children exhibited weaknesses in most macrostructure elements, lexical diversity, syntactic complexity, and three Mandarin-specific microstructure elements.
The study has important clinical implications for speech-language pathologists who work with children speaking Mandarin Chinese. First, the measure of grammaticality was not differentiating between the TD group and the group with LI in Mandarin-speaking children. This is different from children speaking many Indo-European languages where grammaticality was typically sensitive in detecting group membership (e.g., Reilly et al., 2004). When choosing measures to monitor children's language performance, researchers and speech-language pathologists should always take language typology into account and bear in mind that a language with very sparse morphology may inherently lead to fewer opportunities for grammatical violations. Second, clinicians should focus their attention on the areas of identified weaknesses in Mandarin-speaking children with LI, including macrostructure, lexical diversity, syntactic complexity, and the three fine-grained microstructure elements. These areas should be directly targeted when screening children for potential LI and when setting intervention goals. Last but not the least, clinicians should be aware that verbosity is secondary compared to the quality of language production. In storytelling, children with LI may produce a comparable number of utterances and even a comparable number of total words as their age peers, but they are more likely to repeatedly use the same words (i.e., lower lexical diversity), and their sentences may be less densely packed with information (i.e., lower syntactic complexity).
This study has several limitations. Children produced short story samples elicited by the three stories. This yielded a relatively low TNU (about 36 C-units from each child). As such, the current findings should be interpreted with caution and need replication through larger numbers of children and longer narrative samples. Moreover, we conducted multiple comparisons, which increased Type I error. However, we took the Benjamini–Hochberg procedure to protect against Type I error. The findings, thus, should reliably reflect deficits in Mandarin-speaking children with LI.
Future research could explore the effects of different narrative tasks on narrative performance. In this study, we did not model the task of storytelling for children. There is debate about whether a model should be provided to familiarize children with how to tell a story. Heilmann, Miller, and Nockerts (2010)  claimed that the provision of a model enables children to display their best narrative performance. However, Norbury and Bishop (2003)  believed that storytelling without a model provides a more realistic impression of children's abilities to plan and organize stories as it is not shaped by an adult model. Future research could also investigate speech disruption rates (e.g., pauses, vocal hesitations, revisions, and repetitions). Deficits in these measures reflect processing difficulties in retrieving vocabulary and syntactic frames, and children with LI have been found to display higher speech disruption rates in word and sentence retrievals (Guo et al., 2008).
Acknowledgments
This study was supported by the Shanghai Municipal Education Commission (D1502) awarded to Li Sheng, Yiwen Zhang, and Fan Jiang and a Pudong One Hundred Award to Li Sheng. The authors wish to thank all the participating families for their time; Jiandan Huang, Jiaolong Yang, Huilin Chen for their assistance with data collection; and Zijing Yu, Yuxiang Wang, and Li Chen for their assistance with data transcription and interpretation.
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Footnotes
1 To be more precise, “le” is the perfective marker, “guo” is the experiential marker, “zai” is the progressive marker, and “zhe” is the durative marker (Li & Thompson, 1981). However, in general, both “le” and “guo” can be categorized as perfective markers, and both “zai” and “zhe” can be categorized as progressive markers (Klein et al., 2000).
To be more precise, “le” is the perfective marker, “guo” is the experiential marker, “zai” is the progressive marker, and “zhe” is the durative marker (Li & Thompson, 1981). However, in general, both “le” and “guo” can be categorized as perfective markers, and both “zai” and “zhe” can be categorized as progressive markers (Klein et al., 2000).×
2 MENT © 2014 by Bethel Hearing and Speaking Training Center Inc.
MENT © 2014 by Bethel Hearing and Speaking Training Center Inc.×
3 Different IQ cutoff scores have been adopted by researchers (Gallinat & Spaulding, 2014). In our sample, five children with LI scored from 70 to 79. To see whether lower IQ scores changed our findings, we conducted comparisons on all dependent variables between the reduced sample (n = 13) of children with LI and their age matches (all children's IQ scores were above 80). The results from the reduced sample were the same as those from the unreduced sample. Therefore, we included children whose IQ scores were between 70 and 79 to maintain a larger and a more representative sample.
Different IQ cutoff scores have been adopted by researchers (Gallinat & Spaulding, 2014). In our sample, five children with LI scored from 70 to 79. To see whether lower IQ scores changed our findings, we conducted comparisons on all dependent variables between the reduced sample (n = 13) of children with LI and their age matches (all children's IQ scores were above 80). The results from the reduced sample were the same as those from the unreduced sample. Therefore, we included children whose IQ scores were between 70 and 79 to maintain a larger and a more representative sample.×
4 Note that for the current study, we only included narrative samples from the older children, not spontaneous samples from the younger children. The measures used in the validation of the DREAM are different from the measures we selected in the current study. From Liu et al. (2017), they measured the usage of mental verbs and connectives, but we focused on other narrative measures.
Note that for the current study, we only included narrative samples from the older children, not spontaneous samples from the younger children. The measures used in the validation of the DREAM are different from the measures we selected in the current study. From Liu et al. (2017), they measured the usage of mental verbs and connectives, but we focused on other narrative measures.×
5 More specifically, eight children with LI were below 80 in only the expressive component; five were below 80 in all components; four were below 80 in expressive and syntax components; and one was below 80 in all but the expressive component.
More specifically, eight children with LI were below 80 in only the expressive component; five were below 80 in all components; four were below 80 in expressive and syntax components; and one was below 80 in all but the expressive component.×
6 Even though the group difference in TNW was not significant, the p level was low (p = .113), rendering it possible that lower frequencies of the three microstructure elements in children with LI (“bei” sentence, classifier and perfective aspect marker “le”) may have arisen from lower TNW in the group with LI. We conducted group comparisons of the three elements by entering TNW as a covariate. The p levels were 0.055 (“bei” structure), 0.096 (classifier), and 0.006 (perfective marker “le”), respectively, after controlling for TNW.
Even though the group difference in TNW was not significant, the p level was low (p = .113), rendering it possible that lower frequencies of the three microstructure elements in children with LI (“bei” sentence, classifier and perfective aspect marker “le”) may have arisen from lower TNW in the group with LI. We conducted group comparisons of the three elements by entering TNW as a covariate. The p levels were 0.055 (“bei” structure), 0.096 (classifier), and 0.006 (perfective marker “le”), respectively, after controlling for TNW.×
Table 1. Participant information by typicality.
Participant information by typicality.×
Measure LI (n = 18)
TD (n = 18)
t p value
M SD M SD
Age (months;years) 6;2 1;2 6;2 1;1 0.14 .894
Gender: male/female 14/4 10/8
Education 2.33 1.14 3.00 1.28 1.65 .108
IQ 90.44 16.69 98.89 12.31 1.73 .094
DREAM–Total 83.61 9.77 100.61 8.47 5.85 <.001
DREAM–Receptive 84.65 10.57 100.72 9.08 4.53 <.001
DREAM–Expressive 72.44 7.64 98.89 9.88 7.79 <.001
DREAM–Syntax 79.33 7.67 94.06 6.70 6.08 <.001
DREAM–Semantics 87.50 13.00 106.89 11.85 4.99 <.001
Note. Education is presented in scales ranging from 1 to 5: 5 = PhD/master's degree, 4 = bachelor's degree, 3 = associate degree, 2 = high school, 1 = middle school or lower. The IQ scores and DREAM scores are standard scores. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; DREAM = Diagnostic Receptive and Expressive Assessment of Mandarin.
Note. Education is presented in scales ranging from 1 to 5: 5 = PhD/master's degree, 4 = bachelor's degree, 3 = associate degree, 2 = high school, 1 = middle school or lower. The IQ scores and DREAM scores are standard scores. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; DREAM = Diagnostic Receptive and Expressive Assessment of Mandarin.×
Table 1. Participant information by typicality.
Participant information by typicality.×
Measure LI (n = 18)
TD (n = 18)
t p value
M SD M SD
Age (months;years) 6;2 1;2 6;2 1;1 0.14 .894
Gender: male/female 14/4 10/8
Education 2.33 1.14 3.00 1.28 1.65 .108
IQ 90.44 16.69 98.89 12.31 1.73 .094
DREAM–Total 83.61 9.77 100.61 8.47 5.85 <.001
DREAM–Receptive 84.65 10.57 100.72 9.08 4.53 <.001
DREAM–Expressive 72.44 7.64 98.89 9.88 7.79 <.001
DREAM–Syntax 79.33 7.67 94.06 6.70 6.08 <.001
DREAM–Semantics 87.50 13.00 106.89 11.85 4.99 <.001
Note. Education is presented in scales ranging from 1 to 5: 5 = PhD/master's degree, 4 = bachelor's degree, 3 = associate degree, 2 = high school, 1 = middle school or lower. The IQ scores and DREAM scores are standard scores. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; DREAM = Diagnostic Receptive and Expressive Assessment of Mandarin.
Note. Education is presented in scales ranging from 1 to 5: 5 = PhD/master's degree, 4 = bachelor's degree, 3 = associate degree, 2 = high school, 1 = middle school or lower. The IQ scores and DREAM scores are standard scores. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; DREAM = Diagnostic Receptive and Expressive Assessment of Mandarin.×
×
Table 2. Macrostructure scoring rubric and examples.
Macrostructure scoring rubric and examples.×
Macrostructure elements Score
0 1 2 3
Character No character is included or only pronouns are used.
e.g., he, she
Includes characters that are not related to the storyline. Includes one of the two characters. Includes both characters.
e.g., girl, mother
Setting No time or place is stated. Includes at least one time or place that is not related to the storyline. Includes one time or one place that is related to the storyline.
e.g., 1 day, in the fridge
Includes at least two times or two places that are related to the storyline.
Initiating event (IE) A problem or starting event is not stated. Includes events or problems that are not related to the storyline. Includes one event or problem that is related to the primary storyline. e.g., The girl wants to eat it. Includes more than one event or problem that is related to the primary storyline.
Internal response No feelings, desires, or thoughts are stated. Includes expressions of feelings, desires, or thoughts that are not related to the IEs. Includes two feelings, desires, or thoughts that are directly related to the IEs.e.g., The mother thought that it should be put into fridge. Includes more than two feelings, desires, or thoughts that are directly related to the IEs.
Plan No statement is provided about the character's plan to solve the problem. Includes one statement of plan that is not related to the IEs. Includes one statement of plan that is directly related to the IEs.
e.g., She is going to eat it.
Includes at least two statements of plan that are directly related to the IEs.
Action series No action is taken by any of the characters. There are a series of random descriptions.
e.g., A girl. Another girl.
Actions are taken by the characters but are not directly related to the IEs.
e.g., They are boiling eggs. (no such action depicted)
At least one action that is directly related to the IEs is taken by the main character. However, the action series do not form a complete episode. e.g., She gets the cake. Includes a series of actions that are directly related to the IEs and can be formed into a complete episode.
e.g., She is afraid the cake may melt. She gets the cake and moves it into the fridge.
Consequences No consequence is stated. There are statements of consequences, but they are not related to the IEs. Includes one consequence that is directly related to the IEs.
e.g., She puts the cake into the fridge.
Includes at least two consequences that are directly related to the IEs.
Note. The examples are from one of the three stories. The rubric varies for different stories on the basis of the storyline and observations of children's overall performance.
Note. The examples are from one of the three stories. The rubric varies for different stories on the basis of the storyline and observations of children's overall performance.×
Table 2. Macrostructure scoring rubric and examples.
Macrostructure scoring rubric and examples.×
Macrostructure elements Score
0 1 2 3
Character No character is included or only pronouns are used.
e.g., he, she
Includes characters that are not related to the storyline. Includes one of the two characters. Includes both characters.
e.g., girl, mother
Setting No time or place is stated. Includes at least one time or place that is not related to the storyline. Includes one time or one place that is related to the storyline.
e.g., 1 day, in the fridge
Includes at least two times or two places that are related to the storyline.
Initiating event (IE) A problem or starting event is not stated. Includes events or problems that are not related to the storyline. Includes one event or problem that is related to the primary storyline. e.g., The girl wants to eat it. Includes more than one event or problem that is related to the primary storyline.
Internal response No feelings, desires, or thoughts are stated. Includes expressions of feelings, desires, or thoughts that are not related to the IEs. Includes two feelings, desires, or thoughts that are directly related to the IEs.e.g., The mother thought that it should be put into fridge. Includes more than two feelings, desires, or thoughts that are directly related to the IEs.
Plan No statement is provided about the character's plan to solve the problem. Includes one statement of plan that is not related to the IEs. Includes one statement of plan that is directly related to the IEs.
e.g., She is going to eat it.
Includes at least two statements of plan that are directly related to the IEs.
Action series No action is taken by any of the characters. There are a series of random descriptions.
e.g., A girl. Another girl.
Actions are taken by the characters but are not directly related to the IEs.
e.g., They are boiling eggs. (no such action depicted)
At least one action that is directly related to the IEs is taken by the main character. However, the action series do not form a complete episode. e.g., She gets the cake. Includes a series of actions that are directly related to the IEs and can be formed into a complete episode.
e.g., She is afraid the cake may melt. She gets the cake and moves it into the fridge.
Consequences No consequence is stated. There are statements of consequences, but they are not related to the IEs. Includes one consequence that is directly related to the IEs.
e.g., She puts the cake into the fridge.
Includes at least two consequences that are directly related to the IEs.
Note. The examples are from one of the three stories. The rubric varies for different stories on the basis of the storyline and observations of children's overall performance.
Note. The examples are from one of the three stories. The rubric varies for different stories on the basis of the storyline and observations of children's overall performance.×
×
Table 3. Fine-grained microstructure definitions and examples.
Fine-grained microstructure definitions and examples.×
Fine-grained microstructure elements Definitions Examples
Ba Mandarin active sentence structure with a word order “agent + ba + patient + action” (“ba” is obligatory) 弟弟屋顶涂成黄色。
Dìdi bǎ wūding tú chéng huángsè.
Brother ba roof paint resultative yellow.
The younger brother painted the roof yellow.
Bei Mandarin passive sentence structure with a word order “patient + bei + agent + action” (“bei” is obligatory) 梯子他的爸爸拿走了。
Tīzi beì tā de bàba ná zǒu le.
Ladder bei he possessive-particle father carry go-resultative perfective-marker.
The ladder was taken away by his dad.
Negation A negation word negating a word or a sentence (negation words are obligatory) 这个小女孩睡觉。
Zhè gè xiǎo nǚhaí bú shuìjiào.
This classifier little girl no sleep.
This little girl is not sleeping.
Classifier A word in between a number and a noun showing the property of the noun (the generic classifier “ge” was not counted; classifiers are obligatory) 小妹妹搬来了一椅子。
Xiǎo meìmei bān laí le yì ba yǐzi.
Little sister move come-resultative perfective-aspect one classifier chair.
The younger sister brought one chair.
Perfective aspect marker Mandarin perfective aspect “le”/“guo” marker after either a verb or an adjective showing an action or status is completed (perfective aspect markers are optional in some cases) 医生来
Yīshēng laí le.
Doctor come perfective-maker.
The doctor came.
弟弟高
Dìdi gāo le.
Brother tall perfective-marker.
The younger brother became taller.
Progressive aspect marker Mandarin progressive aspect marker “zai/zhe” showing an action is progressing (progressive aspect markers are optional in some cases) 小华刷墙。
Xiǎohuá zaì shuā qiáng.
Xiaohua progressive-marker brush wall.
Xiaohua is painting the wall.
Table 3. Fine-grained microstructure definitions and examples.
Fine-grained microstructure definitions and examples.×
Fine-grained microstructure elements Definitions Examples
Ba Mandarin active sentence structure with a word order “agent + ba + patient + action” (“ba” is obligatory) 弟弟屋顶涂成黄色。
Dìdi bǎ wūding tú chéng huángsè.
Brother ba roof paint resultative yellow.
The younger brother painted the roof yellow.
Bei Mandarin passive sentence structure with a word order “patient + bei + agent + action” (“bei” is obligatory) 梯子他的爸爸拿走了。
Tīzi beì tā de bàba ná zǒu le.
Ladder bei he possessive-particle father carry go-resultative perfective-marker.
The ladder was taken away by his dad.
Negation A negation word negating a word or a sentence (negation words are obligatory) 这个小女孩睡觉。
Zhè gè xiǎo nǚhaí bú shuìjiào.
This classifier little girl no sleep.
This little girl is not sleeping.
Classifier A word in between a number and a noun showing the property of the noun (the generic classifier “ge” was not counted; classifiers are obligatory) 小妹妹搬来了一椅子。
Xiǎo meìmei bān laí le yì ba yǐzi.
Little sister move come-resultative perfective-aspect one classifier chair.
The younger sister brought one chair.
Perfective aspect marker Mandarin perfective aspect “le”/“guo” marker after either a verb or an adjective showing an action or status is completed (perfective aspect markers are optional in some cases) 医生来
Yīshēng laí le.
Doctor come perfective-maker.
The doctor came.
弟弟高
Dìdi gāo le.
Brother tall perfective-marker.
The younger brother became taller.
Progressive aspect marker Mandarin progressive aspect marker “zai/zhe” showing an action is progressing (progressive aspect markers are optional in some cases) 小华刷墙。
Xiǎohuá zaì shuā qiáng.
Xiaohua progressive-marker brush wall.
Xiaohua is painting the wall.
×
Table 4. Comparisons of macrostructure between the group with LI and the TD group.
Comparisons of macrostructure between the group with LI and the TD group.×
Macrostructure elements LI
TD
t p value Cohen's d
M SD M SD
Character 1.55 1.17 2.52 0.54 3.20 .004 a 1.065
Setting 1.87 0.79 2.43 0.57 2.42 .022 a 0.813
Initiating event 2.03 0.84 2.46 0.51 1.88 .071 0.619
Internal response 0.07 0.18 0.76 0.62 4.46 < .001 a 1.511
Plan 0.37 0.56 0.46 0.44 0.55 .588 0.177
Action series 2.02 0.46 2.52 0.46 3.24 .003 a 1.087
Consequence 1.25 0.96 1.98 0.74 2.56 .015 a 0.852
Total 9.16 3.80 13.13 2.46 3.73 .001 a 1.240
Note. All scores were averages of the three stories. All elements were scaled from 0 to 3. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.
Note. All scores were averages of the three stories. All elements were scaled from 0 to 3. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.×
a Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.
Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.×
Table 4. Comparisons of macrostructure between the group with LI and the TD group.
Comparisons of macrostructure between the group with LI and the TD group.×
Macrostructure elements LI
TD
t p value Cohen's d
M SD M SD
Character 1.55 1.17 2.52 0.54 3.20 .004 a 1.065
Setting 1.87 0.79 2.43 0.57 2.42 .022 a 0.813
Initiating event 2.03 0.84 2.46 0.51 1.88 .071 0.619
Internal response 0.07 0.18 0.76 0.62 4.46 < .001 a 1.511
Plan 0.37 0.56 0.46 0.44 0.55 .588 0.177
Action series 2.02 0.46 2.52 0.46 3.24 .003 a 1.087
Consequence 1.25 0.96 1.98 0.74 2.56 .015 a 0.852
Total 9.16 3.80 13.13 2.46 3.73 .001 a 1.240
Note. All scores were averages of the three stories. All elements were scaled from 0 to 3. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.
Note. All scores were averages of the three stories. All elements were scaled from 0 to 3. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.×
a Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.
Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.×
×
Table 5. Comparisons of general microstructure between the group with LI and the TD group.
Comparisons of general microstructure between the group with LI and the TD group.×
General microstructure elements LI
TD
t p value Cohen's d
M SD M SD
MLU 6.18 1.85 7.52 1.36 2.46 .019 a 0.825
NDW 35.19 16.43 47.57 13.22 2.49 .018 a 0.830
TNW 71.38 49.53 93.48 28.79 1.64 .111 0.546
TNU 11.45 5.24 12.70 3.42 0.85 .402 0.283
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; MLU = mean length of utterance; NDW = number of different words; TNW = total number of words; TNU = total number of utterances.
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; MLU = mean length of utterance; NDW = number of different words; TNW = total number of words; TNU = total number of utterances.×
a Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.
Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.×
Table 5. Comparisons of general microstructure between the group with LI and the TD group.
Comparisons of general microstructure between the group with LI and the TD group.×
General microstructure elements LI
TD
t p value Cohen's d
M SD M SD
MLU 6.18 1.85 7.52 1.36 2.46 .019 a 0.825
NDW 35.19 16.43 47.57 13.22 2.49 .018 a 0.830
TNW 71.38 49.53 93.48 28.79 1.64 .111 0.546
TNU 11.45 5.24 12.70 3.42 0.85 .402 0.283
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; MLU = mean length of utterance; NDW = number of different words; TNW = total number of words; TNU = total number of utterances.
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing; MLU = mean length of utterance; NDW = number of different words; TNW = total number of words; TNU = total number of utterances.×
a Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.
Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.×
×
Table 6. Comparisons of fine-grained microstructure between the group with LI and the TD group.
Comparisons of fine-grained microstructure between the group with LI and the TD group.×
Fine-grained microstructure elements LI
TD
t p value Cohen's d
M SD M SD
Ba structure 0.83 1.03 1.04 0.68 0.70 .490 0.240
Bei structure 0.00 0.00 0.13 0.23 2.36 .030 0.810
Negation 1.01 0.66 1.20 0.85 0.73 .472 0.250
Classifier 0.03 0.12 0.37 0.63 2.25 .037 0.750
Perfective aspect marker 2.56 2.11 4.57 1.31 3.45 .002 a 1.145
Progressive aspect marker 0.89 1.11 0.87 0.76 −0.09 .927 −0.021
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.×
a Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.
Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.×
Table 6. Comparisons of fine-grained microstructure between the group with LI and the TD group.
Comparisons of fine-grained microstructure between the group with LI and the TD group.×
Fine-grained microstructure elements LI
TD
t p value Cohen's d
M SD M SD
Ba structure 0.83 1.03 1.04 0.68 0.70 .490 0.240
Bei structure 0.00 0.00 0.13 0.23 2.36 .030 0.810
Negation 1.01 0.66 1.20 0.85 0.73 .472 0.250
Classifier 0.03 0.12 0.37 0.63 2.25 .037 0.750
Perfective aspect marker 2.56 2.11 4.57 1.31 3.45 .002 a 1.145
Progressive aspect marker 0.89 1.11 0.87 0.76 −0.09 .927 −0.021
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.
Note. All scores were averages of the three stories. Independent-samples t tests were conducted to compare the two groups. LI = language impairment; TD = typically developing.×
a Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.
Shows significance after conducting a Benjamini–Hochberg procedure for 18 comparisons. The false discovery rate was at .05.×
×