The Contribution of Two Categories of Parent Verbal Responsiveness to Later Language for Toddlers and Preschoolers on the Autism Spectrum Purpose The authors examined longitudinal associations between 2 categories of parent verbal responsiveness and language comprehension and production 1 year later in 40 toddlers and preschoolers with a diagnosis of an autism spectrum disorder (ASD). Method Parent–child play samples using a standard toy set were digitally captured and ... Research Article
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Research Article  |   February 01, 2013
The Contribution of Two Categories of Parent Verbal Responsiveness to Later Language for Toddlers and Preschoolers on the Autism Spectrum
 
Author Affiliations & Notes
  • Eileen Haebig
    University of Wisconsin—Madison
  • Andrea McDuffie
    University of California, Davis
  • Susan Ellis Weismer
    University of Wisconsin—Madison
  • Correspondence to Eileen Haebig: ehaebig@wisc.edu
  • Editor: Carol Scheffner Hammer
    Editor: Carol Scheffner Hammer×
  • Associate Editor: Nancy Brady
    Associate Editor: Nancy Brady×
Article Information
Special Populations / Autism Spectrum / Research Articles
Research Article   |   February 01, 2013
The Contribution of Two Categories of Parent Verbal Responsiveness to Later Language for Toddlers and Preschoolers on the Autism Spectrum
American Journal of Speech-Language Pathology, February 2013, Vol. 22, 57-70. doi:10.1044/1058-0360(2012/11-0004)
History: Received January 7, 2011 , Revised September 1, 2011 , Accepted July 24, 2012
 
American Journal of Speech-Language Pathology, February 2013, Vol. 22, 57-70. doi:10.1044/1058-0360(2012/11-0004)
History: Received January 7, 2011; Revised September 1, 2011; Accepted July 24, 2012
Web of Science® Times Cited: 17

Purpose The authors examined longitudinal associations between 2 categories of parent verbal responsiveness and language comprehension and production 1 year later in 40 toddlers and preschoolers with a diagnosis of an autism spectrum disorder (ASD).

Method Parent–child play samples using a standard toy set were digitally captured and coded for child engagement with objects and communication acts and for parent verbal responses to play and communication.

Results After controlling for parent education, child engagement, and initial language level, only parent directives for language that followed into the child’s focus of attention accounted for unique variance in predicting both comprehension and production 1 year later. A series of exploratory analyses revealed that parent comments that followed into the child’s focus of attention also accounted for unique variance in later comprehension and production for children who were minimally verbal at the initial time period.

Conclusions Child developmental level may warrant different types of linguistic input to facilitate language learning. Children with ASD who have minimal linguistic skills may benefit from parent language input that follows into the child’s focus of attention. Children with ASD who are verbally fluent may need more advanced language input to facilitate language development.

According to a social interactionist approach to language development, children acquire language through ongoing interactions with conversational partners in everyday contexts (Bohannon & Bonvillian, 2005). For children who face language learning challenges, as do children with an autism spectrum disorder (ASD; American Psychiatric Association, 1994), the contribution of the parent may be especially important in determining the progression of language acquisition. Previous research has provided support for the role of contingent verbal input from parents in supporting language development for children at risk for or experiencing developmental delays (Brady, Marquis, Fleming, & McLean, 2004; Landry, Smith, & Swank, 2006; Mahoney, Boyce, Fewell, Spiker, & Wheeden, 1998; Yoder & Warren, 1999), including children with ASD (McDuffie & Yoder, 2010; Siller & Sigman, 2002, 2008). This study extends the current literature by examining the longitudinal associations between two broad categories of responsive verbal input provided by parents and language skills 12 months later in a group of toddlers and preschoolers with a diagnosis of an ASD.
The hallmark of parent responsiveness is that parents follow into the child’s focus of attention and respond contingently to child acts of play and communication. Parent verbal responsiveness, according to certain theoretical perspectives, is thought to facilitate word learning by providing adult labels that map directly onto the object or activity to which the child is attending (Baldwin, 1995; Tomasello & Farrar, 1986). When parents follow into the child’s focus of attention, they assume the burden of ensuring that both the child and parent are jointly focused on the same referent, creating a state of shared engagement during which parental language input is more likely to be attended to and learned from by the child (e.g., supported joint engagement; Adamson, Bakeman, & Deckner, 2004).
Joint Attention in Children With Autism
Following into the attentional focus of a communication partner, often termed attention following or responding to joint attention, represents a core deficit in children with ASD (Leekam, Hunnisett, & Moore, 1998; Mundy, Sigman, Ungerer, & Sherman, 1986). Indeed, many correlational studies have replicated the predictive association between attention following and later language development for children with ASD (McDuffie, Yoder, & Stone, 2005; Mundy et al., 1986; Sigman & Ruskin, 1999; Siller & Sigman, 2008). Theoretically, the process of attention following allows children to learn the meanings of new words when the adult’s referential focus does not correspond with the child’s. When there is a discrepancy between the adult’s focus of attention and that of the child, the child must notice and respond to adult cues, such as gaze shifts and pointing gestures, to correctly identify the adult’s intended referent. Only then can a correct mapping between novel label and object referent be established. Relative to children with cognitive delays without ASD, experimental studies have shown that children with ASD produce more incorrect mappings between novel labels and objects because they use their own focus of attention, rather than that of the speaker, when acquiring new words (Baron-Cohen, Baldwin, & Crowson, 1997; Preissler & Carey, 2005). Thus, children with ASD often need increased scaffolding during the process of word acquisition. Parent verbal responsiveness can potentially provide needed support to help the child correctly associate new labels with their referents.
Role of Parent Responsiveness
Parent responsiveness may be defined as a broad category of behaviors through which parents provide prompt, affectively positive, and contingent responses to child acts of communication and play (Landry, Smith, Miller-Loncar, & Swank, 1997; Tamis-Lemonda & Bornstein, 2002). Parents who consistently use responsive verbal language input may decrease the cognitive and affective demands on the child to coordinate attention to both people and objects (Adamson et al., 2004). In the present study, two categories of parent verbal responsiveness were examined: responsiveness to the child’s focus of attention and responsiveness to child communication acts.
Responsiveness to the child’s focus of attention. Verbal input that follows into the child’s focus of attention provides labels for objects and events to which the child is actively attending. The facilitative role of follow-in verbal input from parents was considered by Tomasello and Todd (1983), who examined the relationship between early joint attention and language development in typically developing 1-year-olds. These children learned more object labels when mothers followed into and talked about their child’s focus of attention (Landry et al., 1997; Tomasello & Todd, 1983). In fact, within episodes of joint attention, the frequency of labels provided by mothers predicted the child’s later spoken vocabulary (Tomasello & Farrar, 1986). In the present study, we assessed three types of parent verbal responses to the child focus of attention: follow-in commenting, follow-in directives, and parent descriptions of their own actions.
Follow-in comments are statements that describe objects within the child’s focus of attention or with which the child is actively engaged, without conveying an expectation that the child respond to the parent or change his or her current activity. Previous research indicates that follow-in comments predict later language for children with ASD (McDuffie & Yoder, 2010; Siller & Sigman, 2002, 2008). In contrast, follow-in directives—while relating to the child’s ongoing attentional focus—convey an expectation that the child change his or her ongoing activity in some way (e.g., “Throw the ball.”). We consider these types of directive utterances to be follow-in directives for behavior. Although Siller and Sigman (2002)  found no correlation between follow-in directives for behavior and later language, McDuffie and Yoder (2010)  found that follow-in directives for behavior and follow-in comments each contributed unique variance to predicting later vocabulary for a group of toddlers with ASD who produced, on average, fewer than 10 spoken words at the initial study visit.
Following the reasoning of McCathren, Yoder, and Warren (1995), McDuffie and Yoder (2010)  suggested that follow-in directives have the potential to facilitate a mapping between labels and objects or events in a manner similar to follow-in comments, presumably because these types of directives also refer to the child’s current focus of attention. However, McDuffie and Yoder (2010)  assessed follow-in directives only aimed at changing the child’s behavior. Thus, the role of follow-in directives for language (e.g., “What color is that car?”) in supporting later language requires additional clarification. Follow-in directives, which maintain shared focus between parent and child, should be distinguished from redirects, that is, directives that seek to change the child’s focus of attention to correspond to that of the adult. Redirects have been shown to be negatively or nonsignificantly associated with later language (McCathren et al., 1995; McDuffie & Yoder, 2010).
Finally, parents' descriptions of their own actions also can be considered to provide linguistic information about actions that parents are modeling within the child’s focus of attention. If children are actively attending to the parent models, it should be possible to make an association between the parents' actions and the verbal language parents are producing. No previous study, however, has evaluated the contribution of parents' descriptions of their own actions to later language for children with ASD. Examination of this relationship is important as it is likely that parents often may use descriptions of their own actions while engaged in play with their child.
Responsiveness to child communication acts. Child acts of nonverbal and verbal communication clearly indicate the child’s focus of attention to the adult. We examined two types of parent responses to child communication acts: linguistic mapping (Yoder & Warren, 2001) and expansions (Scherer & Olswang, 1984). The adult may respond to nonverbal communication acts by linguistically encoding the child’s presumed message (McDuffie et al., 2005; Siller & Sigman, 2002; Yoder & McDuffie, 2006) or may respond to verbal communication acts by providing additional semantic or grammatical information. During linguistic mapping, the adult provides a noun, verb, or function word that corresponds to the object, action, or event about which the child is communicating. In a similar manner, expansions provide opportunities for children to hear developmentally advanced language forms that map directly onto the child’s own productions. In addition to providing follow-in language input, linguistic mapping and expansions acknowledge the child’s attempts to communicate and may encourage the child to communicate more frequently in subsequent interactions. Yoder and Warren (1999)  found that maternal linguistic mapping mediated the relationship between child intentional communication and later language for a group of children with developmental delays. For a group of minimally verbal children with ASD, McDuffie and Yoder (2010)  found that parent expansions were a unique predictor of later vocabulary size, even after controlling for the frequency of child communication acts.
In summary, certain categories of parent language provided in the context of parent–child interactions (i.e., verbal responsiveness to the child’s focus of attention and verbal responsiveness to child communication acts) have been found to facilitate later language for children with ASD. It is important, however, to acknowledge that opportunities for parents to provide responsive verbal language input is somewhat reliant on child behaviors (i.e., child active engagement and communication acts). As several studies have shown, children with ASD may display a restricted repertoire of play behaviors, which leads to less productive engagement with objects (McDuffie, Lieberman, & Yoder, 2011), and they may initiate communication acts less frequently than children who are typically developing as well as children with other developmental delays (Mundy et al., 1986). Thus, parents may face challenges in having sufficient opportunities to provide responsive verbal language input that responds to child engagement or communication acts. Clinically, this line of research is important as it can inform the content of parent mediated intervention programs, which encourage parents to use empirically based language facilitation strategies when interacting with their children.
The extant literature provides only three published studies examining the relationship between parent verbal responsiveness and subsequent language development for children with ASD (McDuffie & Yoder, 2010; Siller & Sigman, 2002, 2008). Moreover, two of those studies (Siller & Sigman, 2002, 2008) did not examine the role of parent verbal responses to child communication acts in facilitating later language. In addition, Siller and Sigman (2008)  used a composite metric to represent parent responsiveness. This variable included all maternal utterances that were synchronized with the child’s focus of attention (i.e., both follow-in comments and follow-in directives), whereas another variable included only maternal utterances that were synchronized with the child’s focus of attention and action (i.e., follow-in comments). Thus, Siller and Sigman (2008)  did not independently evaluate the role of follow-in directives in predicting either language levels or rate of growth in language over time. In addition, McDuffie and Yoder (2010)  examined language outcomes after only 6 months in time by using a parent report measure of vocabulary comprehension and production. McDuffie and Yoder (2010)  also used a composite variable that collapsed across parent descriptions of their own actions and follow-in comments and coded follow-in directives only for behavior and did not examine the potential contribution of follow-in directives for language. We expanded on these previous studies by using a more nuanced and inclusive coding scheme and by examining longitudinal associations between parent language input and child language outcomes over a period of 1 year.
Research Questions
The following research questions were addressed in a group of toddlers and preschoolers on the autism spectrum:
  1. Does parent language input that follows into the child’s focus of attention significantly predict gains in expressive and receptive language 1 year later?

  2. Does parent language input that responds to child communication acts significantly predict gains in expressive and receptive language?

Method
Overview of Design and Procedure
This study used a longitudinal design. Parent responsivity was coded from videotapes of naturalistic parent–child play samples collected at Time 1 (the initial annual visit of a larger study). Autism status as well as language and cognitive ability were measured at Time 1 and are reported in this article to provide descriptive information about the participants. Although children in the sample demonstrated a range of performance on standardized measures of language and cognition, the mean performance on all measures was in the below-average range. The difference scores (i.e., difference of raw scores between Time 1 and Time 2, on average, 12 months later) from standardized tests of language comprehension and production served as the outcome measures. Parent education was taken into account in all analyses.
Participants
Forty parent–child dyads were selected at random from participants in a larger study examining trajectories of language development in toddlers and preschoolers with ASD. Participants in the larger study were recruited from Wisconsin. All 40 toddlers and preschoolers received a clinical diagnosis of an ASD from an interdisciplinary team of experienced professionals led by a licensed psychologist. Of the 40 participants selected, 33 were boys. The age range of the participants at Time 1 was from 24 to 39 months. All children came from families of native English speakers. Thirty-four of the children were Caucasian, one was Hispanic, two were African American, and three were classified as “other” with respect to racial–ethnic background. Descriptive characteristics of the participants are presented in Table 1.
TABLE 1 Participant characteristics at Time 1 and language outcomes at Time 2.
Participant characteristics at Time 1 and language outcomes at Time 2.×
Measure Total sample (N = 40) MEL group (n = 22) VF group (n = 18)
M SD Range M SD Range M SD Range
Time 1
CA (months) 31.15 4.37 24–39 29.50 4.18 24–37 33.17 3.79 25–39
ADOS severity 7.50 1.81 4–10 8.09 1.90 5–10 6.78 1.44 4–10
NVMAa (months) 24.24 4.64 17–34 21.36 3.40 17–31 27.47 3.64 22–34
CDI WU 151.75 112.92 1–396 103.41 89.08 1–396 210.83 112.82 50–396
CDI WP 60.75 95.54 0–384 7.09 9.04 0–37 126.33 112.06 9–384
PLS–4 AC RS 20.70 6.13 10–42 17.68 2.38 10–22 24.39 7.28 18–42
PLS–4 AC SS 60.20 14.07 50–116 56.27 5.82 50–75 65.00 19.18 50–116
PLS–4 EC RS 25.18 6.15 16–40 20.82 2.54 16–25 30.50 4.91 24–40
PLS–4 EC SS 72.50 11.38 56–106 66.27 6.38 56–79 80.11 11.64 62–106
Parent YOE 14.00 2.04 12–19 13.82 1.92 12–19 14.22 2.21 12–18
Time 2
PLS–4 AC RS 28.42 11.05 17–55 21.59 4.44 17–32 36.78 11.02 20–55
PLS–4 AC SS 64.45 21.53 50–126 51.68 3.70 50–61 80.06 24.04 50–126
PLS–4 EC RS 32.53 9.20 19–56 26.36 5.46 19–39 40.06 6.94 31–56
PLS–4 EC SS 70.85 17.66 50–122 61.14 9.01 50–83 82.72 18.55 54–122
Note.MEL = minimal expressive language; VF = verbally fluent; CA = chronological age; ADOS = Autism Diagnostic Observation Schedule; NVMA = nonverbal mental age; CDI = MacArthur–Bates Communicative Development Inventory; WU = words understood; WP = words produced; PLS–4 = Preschool Language Scales, Fourth Edition; AC = Auditory Comprehension; RS = raw score; SS = standard score; EC = Expressive Communication; YOE = years of education.
Note.MEL = minimal expressive language; VF = verbally fluent; CA = chronological age; ADOS = Autism Diagnostic Observation Schedule; NVMA = nonverbal mental age; CDI = MacArthur–Bates Communicative Development Inventory; WU = words understood; WP = words produced; PLS–4 = Preschool Language Scales, Fourth Edition; AC = Auditory Comprehension; RS = raw score; SS = standard score; EC = Expressive Communication; YOE = years of education.×
aOnly 34 participants had valid data for NVMA.
aOnly 34 participants had valid data for NVMA.×
TABLE 1 Participant characteristics at Time 1 and language outcomes at Time 2.
Participant characteristics at Time 1 and language outcomes at Time 2.×
Measure Total sample (N = 40) MEL group (n = 22) VF group (n = 18)
M SD Range M SD Range M SD Range
Time 1
CA (months) 31.15 4.37 24–39 29.50 4.18 24–37 33.17 3.79 25–39
ADOS severity 7.50 1.81 4–10 8.09 1.90 5–10 6.78 1.44 4–10
NVMAa (months) 24.24 4.64 17–34 21.36 3.40 17–31 27.47 3.64 22–34
CDI WU 151.75 112.92 1–396 103.41 89.08 1–396 210.83 112.82 50–396
CDI WP 60.75 95.54 0–384 7.09 9.04 0–37 126.33 112.06 9–384
PLS–4 AC RS 20.70 6.13 10–42 17.68 2.38 10–22 24.39 7.28 18–42
PLS–4 AC SS 60.20 14.07 50–116 56.27 5.82 50–75 65.00 19.18 50–116
PLS–4 EC RS 25.18 6.15 16–40 20.82 2.54 16–25 30.50 4.91 24–40
PLS–4 EC SS 72.50 11.38 56–106 66.27 6.38 56–79 80.11 11.64 62–106
Parent YOE 14.00 2.04 12–19 13.82 1.92 12–19 14.22 2.21 12–18
Time 2
PLS–4 AC RS 28.42 11.05 17–55 21.59 4.44 17–32 36.78 11.02 20–55
PLS–4 AC SS 64.45 21.53 50–126 51.68 3.70 50–61 80.06 24.04 50–126
PLS–4 EC RS 32.53 9.20 19–56 26.36 5.46 19–39 40.06 6.94 31–56
PLS–4 EC SS 70.85 17.66 50–122 61.14 9.01 50–83 82.72 18.55 54–122
Note.MEL = minimal expressive language; VF = verbally fluent; CA = chronological age; ADOS = Autism Diagnostic Observation Schedule; NVMA = nonverbal mental age; CDI = MacArthur–Bates Communicative Development Inventory; WU = words understood; WP = words produced; PLS–4 = Preschool Language Scales, Fourth Edition; AC = Auditory Comprehension; RS = raw score; SS = standard score; EC = Expressive Communication; YOE = years of education.
Note.MEL = minimal expressive language; VF = verbally fluent; CA = chronological age; ADOS = Autism Diagnostic Observation Schedule; NVMA = nonverbal mental age; CDI = MacArthur–Bates Communicative Development Inventory; WU = words understood; WP = words produced; PLS–4 = Preschool Language Scales, Fourth Edition; AC = Auditory Comprehension; RS = raw score; SS = standard score; EC = Expressive Communication; YOE = years of education.×
aOnly 34 participants had valid data for NVMA.
aOnly 34 participants had valid data for NVMA.×
×
Parents who participated in the play sample procedure consisted of 33 mothers and 7 fathers. Parent education ranged from 12 years to 19 years, with an average of 14 years (SD = 2.04).
Assessments and Measures
Autism status. All participants received a best estimate clinical diagnosis of either autism (n = 17) or autism spectrum (n = 23) from a licensed psychologist who used multiple sources of information, including cognitive and language testing, as well as either the generic (Lord et al., 2000) or toddler version (Luyster et al., 2009) of the Autism Diagnostic Observation Schedule (ADOS) and the Autism Diagnostic Interview—Revised (ADI–R; Le Couteur, Lord, & Rutter, 2003). The ADI–R and ADOS represent the current gold standard for assigning a diagnostic classification of autism for research purposes.
The ADOS consists of a series of activities and materials, presented with systematic prompts and used to elicit a sample of an individual’s social and communication behaviors. There are four ADOS modules, each designed for a particular developmental and language level, ranging from no expressive language in preschool-age children to verbally fluent adults. This system of organization allows the observation to take place within the context of an interaction appropriate for the individual’s expressive language level. The revised ADOS diagnostic algorithms were used, as specified by Gotham and colleagues (Gotham et al., 2008; Gotham, Risi, Pickles, & Lord, 2007). These module-specific algorithms consist of a Social Affective domain (composed of items representing reciprocal social interaction as well as communication) and a Restricted, Repetitive Behaviors domain. Scores for these domains are summed, and the total score is compared with thresholds resulting in an ADOS classification of autism, autism spectrum, or nonspectrum.
To provide additional descriptive information about the participants, we calculated autism severity scores from the ADOS total score according to Gotham, Pickles, and Lord (2009)  and based on each participant’s chronological age, language status, and the ADOS module the participant had received. ADOS severity scores range from 1 to 10, with scores of 1–3, 4–5, and 6–10 indicating mild, moderate, and severe degree of autistic impairment, respectively (Gotham et al., 2009). The diagnosis of an ASD includes individuals who function along a continuum of abilities. To adequately represent this population, participants were not excluded based on scores from language or cognitive measures.
Language and cognition. The MacArthur–Bates Communicative Development Inventory (CDI; Fenson et al., 2007) is a widely used parent report instrument that assesses vocabulary comprehension and production. The Words and Gestures subscale (CDI-WG) contains a vocabulary checklist of 396 words typically acquired by children exposed to American English between 8 and 16 months of age. The Preschool Language Scales, Fourth Edition (PLS–4; Zimmerman, Steiner, & Pond, 2002), is a standardized test of receptive and expressive communication abilities in children ranging from 2 weeks through 6 years of age. Difference scores, computed using Time 1 and Time 2 raw scores for the Auditory Comprehension and Expressive Communication subscales of the PLS, were used as the outcome measures in all analyses. Although it may be difficult to capture change with a standardized measure of global language ability, use of the PLS–4 provided a metric of language comprehension and production that was independent of the contribution of the parent. For a more sensitive measure of change over time, we used raw scores from the PLS–4 rather than age-equivalent or standard scores. Nonverbal cognitive level was assessed with the Visual Reception subscale of the Mullen Scales of Early Learning (MSEL; Mullen, 1995). The MSEL provides a measure of cognitive functioning for infants and children ranging in ages from birth to 68 months.
Procedure
A 15-min parent–child play session was completed at the first visit. During this play session, the child and a parent engaged in play with two different toddler toys (Mr. Potato Head and a Fisher-Price farm set) that were provided by the research team. Before each play sample, the parent was instructed to play with the child as he or she normally would. A student research assistant recorded the play sessions with a handheld digital video recorder.
Coding and Reliability
Play session videos were coded with ProcoderDV (Tapp, 2003). A frequency-based coding procedure was used to code the beginning 10 min of each parent–child play sample. The following child and parent variables were coded: child engagement, parent verbal responses to the child’s focus of attention, child communication acts, and parent verbal responses to child communication acts. Below we provide details of the coding process. Additional details and the coding manual are available from the first author. After coding, data files were exported into MOOSES software (Tapp, Wehby, & Ellis, 1995) for calculation of cumulative frequencies.
Responsiveness to the child’s focus of attention. Parent responsiveness to the child’s focus of attention can be considered part of a transactional process in that the child’s active engagement with toys sets the occasion for the parent to provide language that describes the child’s focus of attention. Thus, coding this category of parent verbal responsiveness required a two-step process: (a) Intervals of child engagement were identified in the play session video; and (b) parent verbal responses that were relevant to the child’s focus of attention were coded.
Child engagement. During the first pass through the media file, each 1-s interval was coded for child active engagement with objects according to a mutually exclusive and exhaustive coding system. Intervals were coded as engaged,not engaged, or uncodable. One-second intervals coded as engaged displayed the child actively manipulating an object or visually attending to an object. Active manipulation of an object was defined as purposeful movement of the object and did not include passive holding. Attention to an object was evident if the child looked at an object or verbalized about an object. The child also was considered to be actively engaged if he or she visually attended to the parent’s use of an object.
Verbal responses to the child’s focus of attention. During the second pass through the media file, instances of parent verbal responsiveness to the child’s focus of attention were identified and coded. Verbal responsiveness to the child’s focus of attention included four subtypes of parent spoken utterances: (a) follow-in comments; (b) parents describing their own action; (c) follow-in directives; and (d) three control variables (redirects, introductions, and other talking). Intervals with continued talking, no talking, or containing unintelligible parent utterances were identified. Each parent utterance was counted only a single time even if the utterance continued across subsequent intervals.
Follow-in comments. The parent was considered to use a follow-in comment if the parent utterance was produced while the child was actively engaged and the comment described the child’s focus of attention. A follow-in comment did not (a) follow a child communication act, (b) tell the child what to do, or (c) request the child to communicate about his or her focus of attention. For example, the parent could say “You’re pushing the tractor” or “There’s the cow, moo moo.”
Parent describes his or her own actions. A parent was credited with describing his or her own action if the parent performed a play action and described this action to the child while the child was attending to what the parent was doing. This type of parent verbal utterance had to be accompanied by a play model; that is, the parent had to demonstrate an action with the toys to which the child was attending (e.g., “Eyes on” as the parent puts the eyes on Mr. Potato Head).
Follow-in directives. Parent directives consisted of parent linguistic input that directed the child (a) to change his or her behavior or (b) to communicate in response to a question. Therefore, follow-in directives included two subtypes of utterances: follow-in directives for behavior (i.e., requests to change a play behavior or toy; e.g., “push the tractor”) and follow-in directives for language (i.e., requests to label an object; e.g., “What’s this?” or “What does the cow say?”).
Control variables. Control variables were included to demonstrate that not all types of parent verbal utterances would be supportive of language growth. Verbal redirects, introductions, and other talking (utterances that did not provide linguistic information about the child’s focus of attention, were not directed toward the child, or did not serve as a redirect or introduction; e.g., “oh” or “mm hm”) were used as control variables.
Responsiveness to child communication acts. Coding this category of parent verbal responsiveness required a two-step process: (a) Acts of child gestural or verbal communication were identified in the play session video; and (b) parent verbal utterances provided subsequent to (within 3 s of) the child communication act were coded.
Child communication acts. Child acts of intentional communication were identified during the first pass through the media files. Child communication acts were defined using the conventions from the Communication and Symbolic Behavior Scales: Developmental Profile (Wetherby & Prizant; 2002). Intentional communication acts could be verbal (i.e., a word or sign) or nonverbal (i.e., communicative gesture or a vocalization with eye gaze). Once child acts of intentional communication were identified, they were categorized as verbal or nonverbal communication acts.
Verbal responses to child communication acts. Following the identification of child acts of intentional communication, the coder determined whether a parent verbal response followed each child communication act within 3 s of the child act. Assuming that a child produced a nonverbal communication act, a parent verbal response was coded as linguistic mapping if the adult labeled a referent or action that was implied by the child’s communication act (e.g., child reaches for the toy cow while shifting eye gaze to the parent and the parent says “want cow”). Additionally, assuming that a verbal act of child intentional communication had occurred, a parent verbal response that expanded the child’s verbal communication act also was recorded (e.g., child says “hat” and the parent expands the child’s communication act by saying “blue hat”).
Refer to Tables 2 and 3 for examples of coded variables and Table 4 for means, ranges, and standard deviations for all coded variables.
TABLE 2 Parent responsiveness to child’s focus of attention.
Parent responsiveness to child’s focus of attention.×
Code Definition Example
Follow-in comments Parent describes child’s action or focus of attention without directing the child to change his or her behavior “You have the piggy!”
“Run, horsey!” (as child moves the horse)
“Moo moo.” (as child plays with the cow)
Parent descriptions of his or her own behavior Parent describes his or her own action with a toy (provided that the child is attending to the parent’s toy) “I’ll put the lips on.” (as parent places lips on Mr. Potato Head)
Follow-in directives for behavior Parent directs the child to change his or her behavior “Put the eyes here.”
“Push the tractor.”
Follow-in directives for language Parent directs the child to produce a communication act (verbal or nonverbal) “What is this?”
“What does the pig say?”
Redirects Parent redirects an engaged child “Look at the cow.” or “Here’s the cow.” (while child is playing with the pig)
Introductions Parent introduces a toy to an unengaged child “I have a hat.”
“See this pig?”
Other talking Other talking “oh” “ok”
TABLE 2 Parent responsiveness to child’s focus of attention.
Parent responsiveness to child’s focus of attention.×
Code Definition Example
Follow-in comments Parent describes child’s action or focus of attention without directing the child to change his or her behavior “You have the piggy!”
“Run, horsey!” (as child moves the horse)
“Moo moo.” (as child plays with the cow)
Parent descriptions of his or her own behavior Parent describes his or her own action with a toy (provided that the child is attending to the parent’s toy) “I’ll put the lips on.” (as parent places lips on Mr. Potato Head)
Follow-in directives for behavior Parent directs the child to change his or her behavior “Put the eyes here.”
“Push the tractor.”
Follow-in directives for language Parent directs the child to produce a communication act (verbal or nonverbal) “What is this?”
“What does the pig say?”
Redirects Parent redirects an engaged child “Look at the cow.” or “Here’s the cow.” (while child is playing with the pig)
Introductions Parent introduces a toy to an unengaged child “I have a hat.”
“See this pig?”
Other talking Other talking “oh” “ok”
×
TABLE 3 Parent verbal responsiveness to child intentional communication acts.
Parent verbal responsiveness to child intentional communication acts.×
Code Description Example
Linguistic mapping Parent puts into words the presumed message of the child’s nonverbal communication act Child: reach for toy cow + eye gaze to adult
Parent: “Cow” or “Want cow”
Expansion Parent repeats what the child said but adds additional linguistic information Child: “Horse”
Parent: “Yellow horse”
TABLE 3 Parent verbal responsiveness to child intentional communication acts.
Parent verbal responsiveness to child intentional communication acts.×
Code Description Example
Linguistic mapping Parent puts into words the presumed message of the child’s nonverbal communication act Child: reach for toy cow + eye gaze to adult
Parent: “Cow” or “Want cow”
Expansion Parent repeats what the child said but adds additional linguistic information Child: “Horse”
Parent: “Yellow horse”
×
TABLE 4 Mean frequencies of child engagement, child communication acts, and parent responsiveness.
Mean frequencies of child engagement, child communication acts, and parent responsiveness.×
Code MEL group (n = 22) VF group (n = 18)
M SD Range M SD Range
Child engagement (in seconds)
 Engaged 529.00 80.87 297–600 533.89 100.51 315–600
 Not engaged 66.50 79.27 0–298 52.11 79.51 0–224
Parent responses to child focus of attention
 FI comments 55.36 24.48 26–111 46.17 28.43 11–128
 Describes action 8.82 5.88 1–24 5.06 4.84 0–17
 No talking 313.73 95.30 137–473 299.94 100.56 151–493
 Other talking 17.36 9.02 3–42 14.28 7.53 3–29
 FI directives (language) 6.09 5.00 0–18 18.28 11.73 2–42
 FI directives (behavior) 12.64 11.00 0–41 16.22 11.11 3–47
 Parent gestures 10.32 8.53 1–36 13.89 9.32 2–37
 Redirect 31.27 17.11 11–78 32.50 16.39 10–88
 Introduction 8.77 12.56 0–57 7.89 11.15 0–37
Child communication acts
 Verbal 1.23 2.11 0–8 33.39 18.39 1–62
 Nonverbal 3.18 3.43 0–12 6.22 6.29 0–20
Parent responses to child communication acts
 Linguistic mapping 1.36 1.84 0–6 2.94 3.11 0–11
 Repetition 0.91 1.69 0–6 9.61 9.06 0–33
 Expansion 0.09 0.29 0–1 4.67 3.27 0–12
Note.FI = follow-in.
Note.FI = follow-in.×
TABLE 4 Mean frequencies of child engagement, child communication acts, and parent responsiveness.
Mean frequencies of child engagement, child communication acts, and parent responsiveness.×
Code MEL group (n = 22) VF group (n = 18)
M SD Range M SD Range
Child engagement (in seconds)
 Engaged 529.00 80.87 297–600 533.89 100.51 315–600
 Not engaged 66.50 79.27 0–298 52.11 79.51 0–224
Parent responses to child focus of attention
 FI comments 55.36 24.48 26–111 46.17 28.43 11–128
 Describes action 8.82 5.88 1–24 5.06 4.84 0–17
 No talking 313.73 95.30 137–473 299.94 100.56 151–493
 Other talking 17.36 9.02 3–42 14.28 7.53 3–29
 FI directives (language) 6.09 5.00 0–18 18.28 11.73 2–42
 FI directives (behavior) 12.64 11.00 0–41 16.22 11.11 3–47
 Parent gestures 10.32 8.53 1–36 13.89 9.32 2–37
 Redirect 31.27 17.11 11–78 32.50 16.39 10–88
 Introduction 8.77 12.56 0–57 7.89 11.15 0–37
Child communication acts
 Verbal 1.23 2.11 0–8 33.39 18.39 1–62
 Nonverbal 3.18 3.43 0–12 6.22 6.29 0–20
Parent responses to child communication acts
 Linguistic mapping 1.36 1.84 0–6 2.94 3.11 0–11
 Repetition 0.91 1.69 0–6 9.61 9.06 0–33
 Expansion 0.09 0.29 0–1 4.67 3.27 0–12
Note.FI = follow-in.
Note.FI = follow-in.×
×
Reliability. Reliability was computed by having a separate coder independently recode 20% of the play samples, which were randomly selected. The primary coder trained the reliability coder through coding of practice videos and a series of consensus discussions. Interobserver reliability was computed using intraclass correlation coefficients. Intraclass correlation coefficients reflect the proportion of the variability in the reliability sample that is due to between-participant variance in true score estimates of the behavior of interest (Shavelson & Webb, 1991). Values of 0.6 are considered acceptable with g coefficients (Suen & Ary, 1989). Reliability between the two coders was .77 for “other talking” and between .956 and 1.0 for all other categories of coded behavior.
Data Analysis
Preliminary data analysis examined bivariate correlations between the Time 1 predictor variables (follow-in comments, follow-in directives, parent descriptions of his or her own action, linguistic mapping, and expansions), the covariates (child engagement, child verbal and nonverbal communication acts, and parent education), control variables (redirects, introductions, and other talking) and difference scores computed from the language measures at both time points (i.e., Time 2 PLS–4 Auditory Comprehension [AC] raw scores minus Time 1 PLS–4 AC raw scores; Time 2 PLS–4 Expressive Communication [EC] raw scores minus Time 1 PLS–4 EC raw scores). Difference scores were used to assess the change or growth in language scores over time. This is necessary given the high degree of intercorrelation between language scores at both time points (i.e., for comprehension, r = .788, p < .001; for production, r = .686, p < .001) and therefore needs to be accounted for. These preliminary analyses were followed by a series of hierarchical multiple regression analyses aimed at identifying unique predictors of later language. Significant predictors from each category of parent responsiveness were entered together as predictors of either comprehension or production difference scores to determine a final regression model. In order to control for engagement when evaluating parent variables that responded to the child’s focus of attention, we created a proportion using the parent responsiveness variable as the numerator and child engagement as the denominator (e.g., follow-in directives for language divided by child engagement). In order to control for the contribution of child communication acts when evaluating the contribution of parent verbal responses to child communication acts, we created a proportion using parent responses to child communication acts as the numerator and child communication acts as the denominator (e.g., parent expansions divided by child verbal communication acts). On the basis of previous research, we expected the coded parent responsive variables to positively relate to language gains; therefore, all analyses were one-tailed.
Results
Bivariate Correlations
Parent responses to child’s focus of attention. Examination of bivariate correlations between parent responses to the child’s focus of attention measured at Time 1 and difference scores for language comprehension (PLS–4 AC) and production (PLS–4 EC) revealed that follow-in comments were not significantly correlated with language gains. Despite this, significant correlations were found between language comprehension difference scores and parent descriptions of his or her own actions (r = −.30) and parent follow-in directives for language (r = .66; all ps < .05, one-tailed). The negative association between parent descriptions of his or her own actions and later language comprehension was unexpected. Only parent follow-in directives for language were significantly associated with language production difference scores (r = .67, p < .05, one-tailed). The association between parent redirects and language comprehension difference scores was in the expected direction but failed to reach significance (r = −.232, p = .075, one-tailed); almost no association was observed for parent redirects and child language production (r = −.083, p = .306, one-tailed).
Parent responses to child communication acts. Bivariate correlations were examined between parent responses to child communication acts at Time 1 and difference scores for language comprehension (PLS–4 AC) and production (PLS–4 EC). Significant bivariate correlations with comprehension were found for expansions (r = .51, p < .001, one-tailed). No significant bivariate correlations were found for language production. (See Table 5 for a summary of all bivariate correlations.)
TABLE 5 Bivariate intercorrelations (N = 40).
Bivariate intercorrelations (N = 40).×
Measure 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1. C—Engagement .35* .16 .30* .03 .17 .33* −.03 .18 −.84** .39** .01 .01 .31* .05
2. C—Nonverbal communication acts .48** .32** .16 −.004 .41** .03 −.20 −.37** .74** .39** .40** .42** .20
3. C- Verbal communication acts −.15 −.18 −.20 .67** .20 −.18 −.13 .36* .82** .12 .67** .26
4. P—Follow-in comments .55** .31* .09 .03 .05 −.24 .52** −.01 .40** −.13 .09
5. P—Descriptive talk of own behavior .23 -.05 .09 −.05 −.04 .28* .02 .23 −.30* −.16
6. P—Other talking −.13 .17 .38** −.02 .14 −.14 .21 −.23 −.26
7. P—Directives for language .36* −.09 −.21 .42** .51** −.05 .66** .40**
8. P—Directives for behavior −.08 −.002 .12 .01 −.085 .14 .15
9. P—Redirects −.14 −.06 −.14 .04 −.23 −.08
10. P—Introductions −.38** .01 −.004 −.14 −.02
11. Linguistic mapping .34* .24 .15 −.01
12. Expansion .11 .51** .18
13. P—Years of education .06 .43**
14. PLS–4 AC difference .50**
15. PLS–4 EC difference
Note.C = child; P = parent.
Note.C = child; P = parent.×
*p < .05. **p < .01.
*p < .05. **p < .01.×
TABLE 5 Bivariate intercorrelations (N = 40).
Bivariate intercorrelations (N = 40).×
Measure 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1. C—Engagement .35* .16 .30* .03 .17 .33* −.03 .18 −.84** .39** .01 .01 .31* .05
2. C—Nonverbal communication acts .48** .32** .16 −.004 .41** .03 −.20 −.37** .74** .39** .40** .42** .20
3. C- Verbal communication acts −.15 −.18 −.20 .67** .20 −.18 −.13 .36* .82** .12 .67** .26
4. P—Follow-in comments .55** .31* .09 .03 .05 −.24 .52** −.01 .40** −.13 .09
5. P—Descriptive talk of own behavior .23 -.05 .09 −.05 −.04 .28* .02 .23 −.30* −.16
6. P—Other talking −.13 .17 .38** −.02 .14 −.14 .21 −.23 −.26
7. P—Directives for language .36* −.09 −.21 .42** .51** −.05 .66** .40**
8. P—Directives for behavior −.08 −.002 .12 .01 −.085 .14 .15
9. P—Redirects −.14 −.06 −.14 .04 −.23 −.08
10. P—Introductions −.38** .01 −.004 −.14 −.02
11. Linguistic mapping .34* .24 .15 −.01
12. Expansion .11 .51** .18
13. P—Years of education .06 .43**
14. PLS–4 AC difference .50**
15. PLS–4 EC difference
Note.C = child; P = parent.
Note.C = child; P = parent.×
*p < .05. **p < .01.
*p < .05. **p < .01.×
×
Hierarchical multiple regressions. Parent behaviors that emerged as significant correlates of language gains in the previous analyses were entered as predictors into a series of hierarchical multiple linear regression analyses to identify parent behaviors that accounted for unique variance in explaining language gains. We included follow-in comments even though they were not significant correlates of either comprehension or production difference scores because of our hypotheses about the importance of this specific variable. The analyses controlled for parent education and, as previously described, engagement and child communication acts were controlled for through the creation of proportions.
Parent variables that responded to the child’s focus of attention. After controlling for parent education, we found that parent follow-in directives for language accounted for significant and unique variance in predicting language comprehension (t = 3.67, p < .001, one-tailed; B = 232.28, β = .59, ΔR2 = .34) and language production (t = 3.10, p = .003, one-tailed; B = 131.43, β = .47, ΔR2 = .22), over and above the contribution of follow-in comments and expansions. Contrary to our expectations, follow-in comments emerged as a negative predictor of language gains for both comprehension (t = −2.231, p = .018, one-tailed; B = −66.157, β = 29.659, ΔR2 = .09) and production (t = −2.312, p = .016, one-tailed; B = −45.862, β = 19.834, ΔR2 = .09).
Parent variables that responded to child communication acts. After controlling for parent education and child verbal communication acts, we found that parent expansions did not significantly contribute to language gains for comprehension, despite significant positive bivariate associations with language comprehension difference scores.
Exploratory Analysis
Because the expected pattern of associations with later language was not observed for parent follow-in comments or expansions, exploratory analyses were undertaken. It was noted that there was considerable variability in Time 1 language abilities within the sample of 40 toddlers. The observation of such diversity in language development corresponds with descriptions in the literature suggesting that children with ASD represent a heterogeneous group in the domain of language development (Lord, Risi, & Pickles, 2004).
Previous intervention research has noted that initial child characteristics often moderate the effectiveness of intervention approaches. Carter and colleagues (2011), for example, found that child outcomes following a parent-implemented language intervention for young children with ASD were moderated by child object interest at the pretreatment (Carter et al., 2011). Children with lower levels of object interest at Time 1 demonstrated language growth, whereas children with higher levels of object interest exhibited attenuated language growth. Child object interest also impacted the effectiveness of different approaches in a randomized comparison of two types of communication interventions (Yoder & Stone, 2006). As initial developmental abilities seem to play a role in language learning (Carter et al., 2011; Yoder & Stone, 2006), it was reasoned that children at different stages of language development might respond differentially to specific types of responsive verbal input from parents. This analysis approach would involve splitting the participant sample into two groups and conducting a regression analysis to determine whether there is an interaction between responsiveness (i.e., parent use of follow-in comments) and group (high language, low language).
We decided that the ADOS administration at Time 1 would provide an objective metric, independent of maternal influence, of the amount of functional spoken language each child used at Time 1. For purposes of the exploratory analysis, children were included in a minimal expressive language (MEL) group (n = 22; autism = 6, ASD = 16) if, on the ADOS Toddler Module or ADOS Module 1, they received a score of 3 or 8 on Item A1, overall level of language. These scores indicate that the child produced fewer than 5 words during administration of the ADOS. Children were included in a verbally fluent (VF) Group (n = 18; autism = 11, ASD = 7) if, on the ADOS Toddler Module or ADOS Module 1, they received a score of 1 or 2 on Item A1. These scores indicate that the child produced at least five recognizable single words or occasionally or regularly produced utterances with at least two words during the ADOS administration. In addition, children who received the ADOS Module 2 were included in the VF group. These children are considered to have the ability to use flexible phrases of at least three words on a regular basis. The MEL subgroup consisted of 17 boys and five girls and 18 mothers and four fathers. The VF subgroup was made up of 16 boys and two girls and 15 mothers and three fathers. Parent education did not differ significantly between the two groups, t(38) = −.619, p = .540, two-tailed. In order to further describe the language ability of participants in these groups, we examined expressive vocabulary as reported by parents on the CDI-WG subscale completed at Time 1. Mean expressive vocabulary sizes were 7.09 (SD = 9.04, range = 0–37) and 126.33 (SD = 112.06, range = 9–384) for the MEL and VF groups, respectively, generally corresponding to the assigned subgroup classification.
The following variables were entered into the regression analysis examining the contribution of follow-in comments to difference scores in comprehension and production: parent education, group (VF, MEL), follow-in comments, and the Group × Follow-in Comments interaction term. To compute the interaction term, we grand mean centered the ratio variable for follow-in comments and dummy coded group (see Cohen, Cohen, West, & Aiken, 2003, p. 261). Grand mean centering is recommended to reduce collinearity between the variables that constitute the product term.
Results of the regression analyses revealed a significant interaction between group and parent use of follow-in comments in predicting language comprehension (t = −2.50, p = .009, one-tailed; B = −105.66, β = 42.32, ΔR2 = .10) and language production (t = −2.54, p = .008, one-tailed; B = −91.38, β = 35.97, ΔR2 = .11). As Figure 1 depicts, after accounting for parent education and child engagement, we found that children with minimal expressive language benefited from parent use of follow-in comments, whereas children who were verbally fluent at the initial visit did not (also see Table 6).
FIGURE 1

Interaction between group and follow-in comments when assessing language production. This figure illustrates that children with an autism spectrum disorder with minimal expressive language benefit from parent follow-in comments in both receptive and expressive domains.

 Interaction between group and follow-in comments when assessing language production. This figure illustrates that children with an autism spectrum disorder with minimal expressive language benefit from parent follow-in comments in both receptive and expressive domains.
FIGURE 1

Interaction between group and follow-in comments when assessing language production. This figure illustrates that children with an autism spectrum disorder with minimal expressive language benefit from parent follow-in comments in both receptive and expressive domains.

×
TABLE 6 Results of multiple regression analyses predicting language gain scores.
Results of multiple regression analyses predicting language gain scores.×
Step Language outcomes
Language comprehensiona Language productionb
ΔR2 B SE B β ΔR2 B SE B β
Step 1 .00 .18**
 Parent years of education 0.22 0.58 .06 1.22 0.42 .43**
Step 2 .34** .09*
 Parent years of education 0.01 0.48 .00 1.14 0.40 .40**
 Group 8.48 1.93 .59** 3.55 1.62 .31*
Step 3 .02 .002
 Parent years of education 0.25 0.53 .07 1.20 0.45 .42**
 Group 7.91 2.00 .55** 3.41 1.70 .30*
 Follow-in comments −25.72 24.34 −.16 −6.46 20.74 −.05
Step 4 .10** .11**
 Parent years of education −0.06 0.51 −.02 0.93 0.43 .33*
 Group 8.09 1.87 .56** 3.56 1.59 .31*
 Follow-in comments 35.33 33.40 .22 46.34 28.38 .39
 Group × Follow-in Comments −105.66 42.32 −.47** −91.38 35.97 −.51**
Note.Parent years of education and follow-in comments were grand mean centered. Ratio values for follow-in comments were used to account for child engagement.
Note.Parent years of education and follow-in comments were grand mean centered. Ratio values for follow-in comments were used to account for child engagement.×
aPLS–4 Auditory Comprehension difference score.
aPLS–4 Auditory Comprehension difference score.×
bPLS–4 Expressive Communication difference score.
bPLS–4 Expressive Communication difference score.×
*p < .05. **p < .01.
*p < .05. **p < .01.×
TABLE 6 Results of multiple regression analyses predicting language gain scores.
Results of multiple regression analyses predicting language gain scores.×
Step Language outcomes
Language comprehensiona Language productionb
ΔR2 B SE B β ΔR2 B SE B β
Step 1 .00 .18**
 Parent years of education 0.22 0.58 .06 1.22 0.42 .43**
Step 2 .34** .09*
 Parent years of education 0.01 0.48 .00 1.14 0.40 .40**
 Group 8.48 1.93 .59** 3.55 1.62 .31*
Step 3 .02 .002
 Parent years of education 0.25 0.53 .07 1.20 0.45 .42**
 Group 7.91 2.00 .55** 3.41 1.70 .30*
 Follow-in comments −25.72 24.34 −.16 −6.46 20.74 −.05
Step 4 .10** .11**
 Parent years of education −0.06 0.51 −.02 0.93 0.43 .33*
 Group 8.09 1.87 .56** 3.56 1.59 .31*
 Follow-in comments 35.33 33.40 .22 46.34 28.38 .39
 Group × Follow-in Comments −105.66 42.32 −.47** −91.38 35.97 −.51**
Note.Parent years of education and follow-in comments were grand mean centered. Ratio values for follow-in comments were used to account for child engagement.
Note.Parent years of education and follow-in comments were grand mean centered. Ratio values for follow-in comments were used to account for child engagement.×
aPLS–4 Auditory Comprehension difference score.
aPLS–4 Auditory Comprehension difference score.×
bPLS–4 Expressive Communication difference score.
bPLS–4 Expressive Communication difference score.×
*p < .05. **p < .01.
*p < .05. **p < .01.×
×
Discussion
For this study, we set out to examine the contributions of specific categories of parent verbal responsiveness to later language outcomes, for a group of young children with diagnoses on the autism spectrum. The types of responsiveness that were examined were based on social interactionist theories of early language learning and previous empirical findings suggesting the types of parent verbal input that should facilitate early language development in children who are challenged in using attention following (i.e., response to joint attention). The most interesting finding of this study was that the relationship between parent linguistic input and later language gains may differ according to the child’s stage of language development.
Responsiveness to the Child’s Focus of Attention
Follow-in commenting. Although parent follow-in comments (i.e., comments that describe the child’s focus of attention without placing demands on the child) were not found to significantly predict later language for the full participant group, the follow-up exploratory analysis revealed an interaction between initial child language levels and parent use of follow-in comments. That is, children who were minimally verbal (in this case, who used fewer than five spoken words during administration of the ADOS) had better language outcomes 1 year later when their parents used more follow-in comments. Children who could be considered verbally fluent (in this case, who used more than five spoken words or talked in multiword utterances) did not benefit from parent use of this type of verbal input and in fact showed attenuated language growth.
The positive association between parent follow-in comments and later language in the group with minimal expressive language replicates and adds support to the findings of McDuffie and Yoder (2010)  and Siller and Sigman (2002) . Furthermore, it appears that participants in the McDuffie and Yoder (2010)  study, who were described as having fewer than 10 words during a conversational language sample, had similar language levels to the participants in the MEL group in the present study. Conversely, participants in the VF group, who all were producing flexible (i.e., nonstereotyped) phrase speech and who had an average spoken vocabulary size of 126 words according to parent report, were more competent communicators and may have benefited more from advanced linguistic input from their parents, rather than follow-in commenting. Furthermore, it is possible that parents were providing labels for objects that the VF group already knew and did not provide sufficient novel verbal information, which may have contributed to the finding of attenuated growth. Carter and colleagues (2011)  suggested that children with ASD with more severe impairments also differentially responded to parent input. Like Carter et al. (2011), our findings suggest that distinct categories of parent language input may support language growth dissimilarly for children at different stages of language acquisition.
Children with lower linguistic abilities produce limited nonverbal and verbal communication acts and therefore have fewer ways of eliciting language-facilitating verbal input from their parents. This highlights the importance of having parents who talk about the child’s focus of attention (i.e., follow-in commenting). Indeed, this group of children had an average spoken vocabulary size of fewer than eight words according to parent report. Parent follow-in commenting, in particular, is not contingent on child communication acts and does not require the child to make an active contribution to the language learning process; instead, the parent actively coordinates his or her own focus of attention and verbal content to match the child’s focus. Therefore, parent descriptions of their child’s focus of attention may optimally support language development for minimally verbal children on the autism spectrum.
Parent descriptions of his or her own behavior. Whereas McDuffie and Yoder (2010)  used a composite variable that included parent descriptions of his or her own actions within the category of parent follow-in comments, the present study examined these two categories of verbal responsiveness separately. We did expect that parent descriptions of his or her own actions while the child was attending to the parent would positively relate to language gains over time. However, we did not find that parent descriptions of his or her actions were related to language gains for this group of children. We speculate that it is not necessarily the case that children will process language input that encodes what the parent is doing, even if it appears that the child is attending to such input. It seems plausible that children with ASD have a more difficult time mapping labels to objects that they are not manipulating themselves and to actions they are not performing even if the child seems to be attending to the action that another person is performing. In addition, although children were judged to be engaged in the interaction during the intervals within which parent descriptions of his or her own actions were observed, it may be difficult to gauge a child’s actual degree of engagement unless the child is actively manipulating an object.
Follow-in directives for language. One difficulty in interpreting the contribution of directives to later language is that previous research often has not distinguished between different types of directives (e.g., redirects, introductions, directives for behavior, and directives for language; McCathren et al., 1995). We tested the contribution of four specific types of directives: redirects, introductions, follow-in directives for behavior, and follow-in directives for language. Follow-in directives for language were significantly and positively associated with later language. Although we found follow-in directives to be facilitative, there remain conflicting suggestions in the literature concerning the contribution of directives to later language. Some propose that use of questions may limit the child to a yes/no response or to producing a label that the child already knows (Whitehurst et al., 1988). Conversely, others have suggested that questions serve as a means to intellectually stimulate children and, by conveying the expectation that the child should respond to the adult, to encourage the child’s participation in a conversational exchange (McDonald & Pien, 1982). Follow-in directives for language can scaffold child engagement with both people and objects (Yoder, Davies, Bishop, & Munson, 1994). In fact, Yoder and colleagues (1994)  found that children with developmental delays were more than twice as likely to continue a topic after an adult produced a follow-in directive for language than in response to a follow-in comment.
Follow-in directives for language may act to promote continuation of the child’s focus of attention because they are contingent on the child’s current focus of attention. In addition, follow-in directives for language may prompt the child to use a known word to label a different exemplar of a referent or to use the word in a different context. This type of generalization may be especially important for children with ASD whose speech is often context bound and for whom words are often not used flexibly (Yoder & McDuffie, 2006). Also, follow-in directives for language may provide a technique that encourages reciprocal exchanges and sharing of attention in children with ASD, a prompt that is needed given these children’s known deficits in initiating joint attention (Mundy et al., 1986). Parent questions that elicit a word that is within the child’s lexicon can be followed with a semantic or grammatical expansion of the child’s prompted response (Scherer & Olswang, 1984; Whitehurst et al., 1988). This point is especially meaningful for our VF group, who likely had a sufficient amount of verbal skills to successfully respond to parent follow-in directives for language. Children who have minimal expressive abilities also may benefit from directives for language because parents can ask questions to prompt nonverbal communication acts and then linguistically map or verbally state the child’s nonverbal message (e.g., when a parent asks, “Where is Mr. Potato Head’s nose?,” the child points to it, and the parent then says, “There’s his nose!”). Thus, because follow-in directives for language can be used to facilitate language in both verbally fluent and minimally verbal children, it is not surprising that positive associations were seen for the entire participant group.
Follow-in directives for behavior. Because children with ASD have restricted and repetitive behaviors and limited play skills (Tager-Flusberg, Joseph, & Folstein, 2001), parents may have infrequent opportunities to use diverse lexical input when providing follow-in comments that describe the child’s focus of attention. On the basis of the findings of McDuffie and Yoder (2010), we hypothesized that follow-in directives for behavior would be facilitative of language acquisition because they instruct the child to play with a toy in a new way or extend current play actions to a new toy. Contrary to our expectations, we did not find a positive association between follow-in directives for behavior and later language. Directives that instruct the child to change his or her behavior may be at odds with the child’s intended actions, and therefore the child may be less likely find this type of parent verbal input to be meaningful.
Responsiveness to Child Communication Acts
Linguistic mapping. Although there is both theoretical and empirical support for the facilitative role of linguistic mapping in supporting language in children with other types of developmental delay (e.g., Yoder & Warren, 1999), researchers have not yet demonstrated that children with ASD can benefit from this type of responsive input. A significant positive correlation between linguistic mapping and later language was observed for the combined participant group for language comprehension. However, after controlling for parent education and accounting for initial child language and frequency of child nonverbal communication acts, we found that linguistic mapping failed to emerge as a significant predictor of later language. On closer examination, it was clear that the opportunity for linguistic mapping was extremely limited in both groups. On average, the combined group of participants produced less than one nonverbal communication act every 2 min during the play sample. In addition, only 26 of the 40 parents ever produced an act of linguistic mapping, with 11 parents producing only one instance of this type of response. Thus, children may not have been exposed to sufficient quantities of linguistic mapping to make a positive contribution to later language.
Expansions. Positive bivariate associations with later language comprehension and expansions were detected, a finding in agreement with previous work (e.g., McDuffie & Yoder, 2010). However, such an association did not persist after controlling for parent education, initial child language, and child verbal communication acts. The opportunity to expand child utterances is dependent on the verbal communication acts produced by the child. These opportunities also were extremely limited given low frequency of child verbal communication acts. On average, the combined group of participants produced one to two verbal communication acts every minute during the play sample, but there was a large range in performance, with about half of the children producing three or fewer verbal communication acts in the entire play sample.
Lack of a positive association between parent expansions and later language in children with ASD also may be related to limitations in attention and motivation (Dawson et al., 2004; Lovaas, Koegel, & Schreibman, 1979). These deficits may impede children’s ability to compare their own communicative productions with the parents' more linguistically advanced model. Young children with autism learned linguistic skills better in adult recast and prompted child imitation conditions than in adult recast-alone conditions (Koegel, Lyons, & Koegel, 2013). Although children with ASD can learn through their interactions with others, they may benefit more from direct prompting than from linguistic mapping and expanding alone. Therefore, both direct prompts for language, such as follow-in directives for language and direct prompts for imitations, may be required with this population.
Limitations of the Current Study
Several limitations must be acknowledged. A large number of variables were investigated given the number of participants in the regression analyses, though a maximum of four variables were considered within each given model in line with statistical guidelines for these types of analyses. In addition, the PLS–4 is not without drawbacks in measuring child language outcomes. The PLS–4 assesses a more developmentally advanced range of language skills in children. One could argue that parent follow-in comments, along with the other types of parent responsiveness examined in this study (e.g., linguistic mapping), mainly consist of object and action labels, which can be expected to specifically and directly build vocabulary but not grammar. Lexical learning might not be well indexed by the PLS–4. Therefore, it may be that a more comprehensive measure of vocabulary (e.g., the CDI) is more useful when studying children with beginning language skills; however, such a measure was not administered at Time 2. Indeed, some may argue that use of a parent report instrument is not appropriate for a study of parent responsiveness as more responsive parents may systematically differ from less responsive parents when reporting their children’s word knowledge. In addition, such a measure may overestimate functional communication abilities in children with ASD. The PLS–4 might have been most appropriate for the VF group, which, according to the ADOS module administered, was already combining words into phrases or sentences and used an average of over 126 words according to parent report at Time 1.
Finally, coding of the initial parent–child observation was limited to just 10 min of a 15-min interaction, which may not be adequate to represent the nature of parent–child interactions. It could be argued that it would have been ideal to capture and analyze a longer sample for each dyad to provide a more representative picture of the parent–child interaction or to capture the language sample in a more familiar or naturalistic environment. However, previous studies assessing parent verbal responsiveness have coded play samples of similar or shorter durations than those used in the current study (e.g., McDuffie and Yoder [2010]  coded 15 min, and Siller and Sigman [2002]  coded 2 min), and use of a laboratory-based sample allowed standardization of the language sampling procedures. We do recognize, though, that other groups of researchers have collected longer samples or have used brief samples collected across different contexts (e.g., Warren, Brady, Sterling, Fleming, & Marquis, 2010). How much time is needed to collect a representative sample is an empirical question that needs to be addressed through further research.
Clinical Implications
Responsive techniques that may be beneficial for use in clinical practice and as targets in parent-mediated intervention programs were identified. The most compelling finding indicated that children may benefit more from particular kinds of parent input during different stages of language development. Specifically, the findings suggest that follow-in comments may be especially beneficial to young children with ASD at the earliest stages of language learning. This is particularly important given that many often assume that children with more severe disabilities are less likely to benefit from intervention or stimulating input, and, therefore, more vigorous services are sometimes directed toward children with less significant disabilities because they may seem more “ready to learn.” Our findings, along with the findings of other research (e.g., Carter et al., 2011; Yoder & Stone, 2006), refute this misconception and stress the value of meaningful input for children who have more severe impairments. In addition, follow-in directives, in the form of questions that the child has the lexical knowledge to answer, may help to support the child’s use of his or her own linguistic knowledge within an interactive context. As discussed by Scherer and Olswang (1984), follow-in directives may be necessary to prompt child verbal communication acts, which subsequently allow opportunities for parents to expand the child’s communicative message. When parents ask their child a question, it is important for them to recognize that that the child’s response sets the occasion for parents to provide additional language input by expanding the child’s response.
Future Directions
This study used child language outcomes that were measured 1 year following the initial visit. It would be beneficial to assess language outcomes at subsequent points of time through longer term longitudinal studies. Alternatively, treatment studies can teach parents of children with ASD to increase parent responsiveness and assess child language outcomes to demonstrate a causal relationship between the two. Previous studies have shown that parents of children with ASD can learn to use language facilitation strategies (Carter et al., 2011; Venker, McDuffie, Ellis Weismer, & Abbeduto, 2011). Future studies should focus on demonstrating that a causal relationship between a parent-mediated intervention program and child language outcomes is indeed mediated through gains in parent responsivity.
Acknowledgments
Funding for this project was provided by National Institutes of Health Grants R01 DC007223 and T32 DC05359-06 (Susan Ellis Weismer, principal investigator), as well as by a core grant, P30 HD03352, to support the Waisman Center (Marsha Seltzer, principal investigator). We sincerely appreciate the contribution of the families who participated in this study. Also, we thank Amy Stern for her valuable help.
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FIGURE 1

Interaction between group and follow-in comments when assessing language production. This figure illustrates that children with an autism spectrum disorder with minimal expressive language benefit from parent follow-in comments in both receptive and expressive domains.

 Interaction between group and follow-in comments when assessing language production. This figure illustrates that children with an autism spectrum disorder with minimal expressive language benefit from parent follow-in comments in both receptive and expressive domains.
FIGURE 1

Interaction between group and follow-in comments when assessing language production. This figure illustrates that children with an autism spectrum disorder with minimal expressive language benefit from parent follow-in comments in both receptive and expressive domains.

×
TABLE 1 Participant characteristics at Time 1 and language outcomes at Time 2.
Participant characteristics at Time 1 and language outcomes at Time 2.×
Measure Total sample (N = 40) MEL group (n = 22) VF group (n = 18)
M SD Range M SD Range M SD Range
Time 1
CA (months) 31.15 4.37 24–39 29.50 4.18 24–37 33.17 3.79 25–39
ADOS severity 7.50 1.81 4–10 8.09 1.90 5–10 6.78 1.44 4–10
NVMAa (months) 24.24 4.64 17–34 21.36 3.40 17–31 27.47 3.64 22–34
CDI WU 151.75 112.92 1–396 103.41 89.08 1–396 210.83 112.82 50–396
CDI WP 60.75 95.54 0–384 7.09 9.04 0–37 126.33 112.06 9–384
PLS–4 AC RS 20.70 6.13 10–42 17.68 2.38 10–22 24.39 7.28 18–42
PLS–4 AC SS 60.20 14.07 50–116 56.27 5.82 50–75 65.00 19.18 50–116
PLS–4 EC RS 25.18 6.15 16–40 20.82 2.54 16–25 30.50 4.91 24–40
PLS–4 EC SS 72.50 11.38 56–106 66.27 6.38 56–79 80.11 11.64 62–106
Parent YOE 14.00 2.04 12–19 13.82 1.92 12–19 14.22 2.21 12–18
Time 2
PLS–4 AC RS 28.42 11.05 17–55 21.59 4.44 17–32 36.78 11.02 20–55
PLS–4 AC SS 64.45 21.53 50–126 51.68 3.70 50–61 80.06 24.04 50–126
PLS–4 EC RS 32.53 9.20 19–56 26.36 5.46 19–39 40.06 6.94 31–56
PLS–4 EC SS 70.85 17.66 50–122 61.14 9.01 50–83 82.72 18.55 54–122
Note.MEL = minimal expressive language; VF = verbally fluent; CA = chronological age; ADOS = Autism Diagnostic Observation Schedule; NVMA = nonverbal mental age; CDI = MacArthur–Bates Communicative Development Inventory; WU = words understood; WP = words produced; PLS–4 = Preschool Language Scales, Fourth Edition; AC = Auditory Comprehension; RS = raw score; SS = standard score; EC = Expressive Communication; YOE = years of education.
Note.MEL = minimal expressive language; VF = verbally fluent; CA = chronological age; ADOS = Autism Diagnostic Observation Schedule; NVMA = nonverbal mental age; CDI = MacArthur–Bates Communicative Development Inventory; WU = words understood; WP = words produced; PLS–4 = Preschool Language Scales, Fourth Edition; AC = Auditory Comprehension; RS = raw score; SS = standard score; EC = Expressive Communication; YOE = years of education.×
aOnly 34 participants had valid data for NVMA.
aOnly 34 participants had valid data for NVMA.×
TABLE 1 Participant characteristics at Time 1 and language outcomes at Time 2.
Participant characteristics at Time 1 and language outcomes at Time 2.×
Measure Total sample (N = 40) MEL group (n = 22) VF group (n = 18)
M SD Range M SD Range M SD Range
Time 1
CA (months) 31.15 4.37 24–39 29.50 4.18 24–37 33.17 3.79 25–39
ADOS severity 7.50 1.81 4–10 8.09 1.90 5–10 6.78 1.44 4–10
NVMAa (months) 24.24 4.64 17–34 21.36 3.40 17–31 27.47 3.64 22–34
CDI WU 151.75 112.92 1–396 103.41 89.08 1–396 210.83 112.82 50–396
CDI WP 60.75 95.54 0–384 7.09 9.04 0–37 126.33 112.06 9–384
PLS–4 AC RS 20.70 6.13 10–42 17.68 2.38 10–22 24.39 7.28 18–42
PLS–4 AC SS 60.20 14.07 50–116 56.27 5.82 50–75 65.00 19.18 50–116
PLS–4 EC RS 25.18 6.15 16–40 20.82 2.54 16–25 30.50 4.91 24–40
PLS–4 EC SS 72.50 11.38 56–106 66.27 6.38 56–79 80.11 11.64 62–106
Parent YOE 14.00 2.04 12–19 13.82 1.92 12–19 14.22 2.21 12–18
Time 2
PLS–4 AC RS 28.42 11.05 17–55 21.59 4.44 17–32 36.78 11.02 20–55
PLS–4 AC SS 64.45 21.53 50–126 51.68 3.70 50–61 80.06 24.04 50–126
PLS–4 EC RS 32.53 9.20 19–56 26.36 5.46 19–39 40.06 6.94 31–56
PLS–4 EC SS 70.85 17.66 50–122 61.14 9.01 50–83 82.72 18.55 54–122
Note.MEL = minimal expressive language; VF = verbally fluent; CA = chronological age; ADOS = Autism Diagnostic Observation Schedule; NVMA = nonverbal mental age; CDI = MacArthur–Bates Communicative Development Inventory; WU = words understood; WP = words produced; PLS–4 = Preschool Language Scales, Fourth Edition; AC = Auditory Comprehension; RS = raw score; SS = standard score; EC = Expressive Communication; YOE = years of education.
Note.MEL = minimal expressive language; VF = verbally fluent; CA = chronological age; ADOS = Autism Diagnostic Observation Schedule; NVMA = nonverbal mental age; CDI = MacArthur–Bates Communicative Development Inventory; WU = words understood; WP = words produced; PLS–4 = Preschool Language Scales, Fourth Edition; AC = Auditory Comprehension; RS = raw score; SS = standard score; EC = Expressive Communication; YOE = years of education.×
aOnly 34 participants had valid data for NVMA.
aOnly 34 participants had valid data for NVMA.×
×
TABLE 2 Parent responsiveness to child’s focus of attention.
Parent responsiveness to child’s focus of attention.×
Code Definition Example
Follow-in comments Parent describes child’s action or focus of attention without directing the child to change his or her behavior “You have the piggy!”
“Run, horsey!” (as child moves the horse)
“Moo moo.” (as child plays with the cow)
Parent descriptions of his or her own behavior Parent describes his or her own action with a toy (provided that the child is attending to the parent’s toy) “I’ll put the lips on.” (as parent places lips on Mr. Potato Head)
Follow-in directives for behavior Parent directs the child to change his or her behavior “Put the eyes here.”
“Push the tractor.”
Follow-in directives for language Parent directs the child to produce a communication act (verbal or nonverbal) “What is this?”
“What does the pig say?”
Redirects Parent redirects an engaged child “Look at the cow.” or “Here’s the cow.” (while child is playing with the pig)
Introductions Parent introduces a toy to an unengaged child “I have a hat.”
“See this pig?”
Other talking Other talking “oh” “ok”
TABLE 2 Parent responsiveness to child’s focus of attention.
Parent responsiveness to child’s focus of attention.×
Code Definition Example
Follow-in comments Parent describes child’s action or focus of attention without directing the child to change his or her behavior “You have the piggy!”
“Run, horsey!” (as child moves the horse)
“Moo moo.” (as child plays with the cow)
Parent descriptions of his or her own behavior Parent describes his or her own action with a toy (provided that the child is attending to the parent’s toy) “I’ll put the lips on.” (as parent places lips on Mr. Potato Head)
Follow-in directives for behavior Parent directs the child to change his or her behavior “Put the eyes here.”
“Push the tractor.”
Follow-in directives for language Parent directs the child to produce a communication act (verbal or nonverbal) “What is this?”
“What does the pig say?”
Redirects Parent redirects an engaged child “Look at the cow.” or “Here’s the cow.” (while child is playing with the pig)
Introductions Parent introduces a toy to an unengaged child “I have a hat.”
“See this pig?”
Other talking Other talking “oh” “ok”
×
TABLE 3 Parent verbal responsiveness to child intentional communication acts.
Parent verbal responsiveness to child intentional communication acts.×
Code Description Example
Linguistic mapping Parent puts into words the presumed message of the child’s nonverbal communication act Child: reach for toy cow + eye gaze to adult
Parent: “Cow” or “Want cow”
Expansion Parent repeats what the child said but adds additional linguistic information Child: “Horse”
Parent: “Yellow horse”
TABLE 3 Parent verbal responsiveness to child intentional communication acts.
Parent verbal responsiveness to child intentional communication acts.×
Code Description Example
Linguistic mapping Parent puts into words the presumed message of the child’s nonverbal communication act Child: reach for toy cow + eye gaze to adult
Parent: “Cow” or “Want cow”
Expansion Parent repeats what the child said but adds additional linguistic information Child: “Horse”
Parent: “Yellow horse”
×
TABLE 4 Mean frequencies of child engagement, child communication acts, and parent responsiveness.
Mean frequencies of child engagement, child communication acts, and parent responsiveness.×
Code MEL group (n = 22) VF group (n = 18)
M SD Range M SD Range
Child engagement (in seconds)
 Engaged 529.00 80.87 297–600 533.89 100.51 315–600
 Not engaged 66.50 79.27 0–298 52.11 79.51 0–224
Parent responses to child focus of attention
 FI comments 55.36 24.48 26–111 46.17 28.43 11–128
 Describes action 8.82 5.88 1–24 5.06 4.84 0–17
 No talking 313.73 95.30 137–473 299.94 100.56 151–493
 Other talking 17.36 9.02 3–42 14.28 7.53 3–29
 FI directives (language) 6.09 5.00 0–18 18.28 11.73 2–42
 FI directives (behavior) 12.64 11.00 0–41 16.22 11.11 3–47
 Parent gestures 10.32 8.53 1–36 13.89 9.32 2–37
 Redirect 31.27 17.11 11–78 32.50 16.39 10–88
 Introduction 8.77 12.56 0–57 7.89 11.15 0–37
Child communication acts
 Verbal 1.23 2.11 0–8 33.39 18.39 1–62
 Nonverbal 3.18 3.43 0–12 6.22 6.29 0–20
Parent responses to child communication acts
 Linguistic mapping 1.36 1.84 0–6 2.94 3.11 0–11
 Repetition 0.91 1.69 0–6 9.61 9.06 0–33
 Expansion 0.09 0.29 0–1 4.67 3.27 0–12
Note.FI = follow-in.
Note.FI = follow-in.×
TABLE 4 Mean frequencies of child engagement, child communication acts, and parent responsiveness.
Mean frequencies of child engagement, child communication acts, and parent responsiveness.×
Code MEL group (n = 22) VF group (n = 18)
M SD Range M SD Range
Child engagement (in seconds)
 Engaged 529.00 80.87 297–600 533.89 100.51 315–600
 Not engaged 66.50 79.27 0–298 52.11 79.51 0–224
Parent responses to child focus of attention
 FI comments 55.36 24.48 26–111 46.17 28.43 11–128
 Describes action 8.82 5.88 1–24 5.06 4.84 0–17
 No talking 313.73 95.30 137–473 299.94 100.56 151–493
 Other talking 17.36 9.02 3–42 14.28 7.53 3–29
 FI directives (language) 6.09 5.00 0–18 18.28 11.73 2–42
 FI directives (behavior) 12.64 11.00 0–41 16.22 11.11 3–47
 Parent gestures 10.32 8.53 1–36 13.89 9.32 2–37
 Redirect 31.27 17.11 11–78 32.50 16.39 10–88
 Introduction 8.77 12.56 0–57 7.89 11.15 0–37
Child communication acts
 Verbal 1.23 2.11 0–8 33.39 18.39 1–62
 Nonverbal 3.18 3.43 0–12 6.22 6.29 0–20
Parent responses to child communication acts
 Linguistic mapping 1.36 1.84 0–6 2.94 3.11 0–11
 Repetition 0.91 1.69 0–6 9.61 9.06 0–33
 Expansion 0.09 0.29 0–1 4.67 3.27 0–12
Note.FI = follow-in.
Note.FI = follow-in.×
×
TABLE 5 Bivariate intercorrelations (N = 40).
Bivariate intercorrelations (N = 40).×
Measure 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1. C—Engagement .35* .16 .30* .03 .17 .33* −.03 .18 −.84** .39** .01 .01 .31* .05
2. C—Nonverbal communication acts .48** .32** .16 −.004 .41** .03 −.20 −.37** .74** .39** .40** .42** .20
3. C- Verbal communication acts −.15 −.18 −.20 .67** .20 −.18 −.13 .36* .82** .12 .67** .26
4. P—Follow-in comments .55** .31* .09 .03 .05 −.24 .52** −.01 .40** −.13 .09
5. P—Descriptive talk of own behavior .23 -.05 .09 −.05 −.04 .28* .02 .23 −.30* −.16
6. P—Other talking −.13 .17 .38** −.02 .14 −.14 .21 −.23 −.26
7. P—Directives for language .36* −.09 −.21 .42** .51** −.05 .66** .40**
8. P—Directives for behavior −.08 −.002 .12 .01 −.085 .14 .15
9. P—Redirects −.14 −.06 −.14 .04 −.23 −.08
10. P—Introductions −.38** .01 −.004 −.14 −.02
11. Linguistic mapping .34* .24 .15 −.01
12. Expansion .11 .51** .18
13. P—Years of education .06 .43**
14. PLS–4 AC difference .50**
15. PLS–4 EC difference
Note.C = child; P = parent.
Note.C = child; P = parent.×
*p < .05. **p < .01.
*p < .05. **p < .01.×
TABLE 5 Bivariate intercorrelations (N = 40).
Bivariate intercorrelations (N = 40).×
Measure 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1. C—Engagement .35* .16 .30* .03 .17 .33* −.03 .18 −.84** .39** .01 .01 .31* .05
2. C—Nonverbal communication acts .48** .32** .16 −.004 .41** .03 −.20 −.37** .74** .39** .40** .42** .20
3. C- Verbal communication acts −.15 −.18 −.20 .67** .20 −.18 −.13 .36* .82** .12 .67** .26
4. P—Follow-in comments .55** .31* .09 .03 .05 −.24 .52** −.01 .40** −.13 .09
5. P—Descriptive talk of own behavior .23 -.05 .09 −.05 −.04 .28* .02 .23 −.30* −.16
6. P—Other talking −.13 .17 .38** −.02 .14 −.14 .21 −.23 −.26
7. P—Directives for language .36* −.09 −.21 .42** .51** −.05 .66** .40**
8. P—Directives for behavior −.08 −.002 .12 .01 −.085 .14 .15
9. P—Redirects −.14 −.06 −.14 .04 −.23 −.08
10. P—Introductions −.38** .01 −.004 −.14 −.02
11. Linguistic mapping .34* .24 .15 −.01
12. Expansion .11 .51** .18
13. P—Years of education .06 .43**
14. PLS–4 AC difference .50**
15. PLS–4 EC difference
Note.C = child; P = parent.
Note.C = child; P = parent.×
*p < .05. **p < .01.
*p < .05. **p < .01.×
×
TABLE 6 Results of multiple regression analyses predicting language gain scores.
Results of multiple regression analyses predicting language gain scores.×
Step Language outcomes
Language comprehensiona Language productionb
ΔR2 B SE B β ΔR2 B SE B β
Step 1 .00 .18**
 Parent years of education 0.22 0.58 .06 1.22 0.42 .43**
Step 2 .34** .09*
 Parent years of education 0.01 0.48 .00 1.14 0.40 .40**
 Group 8.48 1.93 .59** 3.55 1.62 .31*
Step 3 .02 .002
 Parent years of education 0.25 0.53 .07 1.20 0.45 .42**
 Group 7.91 2.00 .55** 3.41 1.70 .30*
 Follow-in comments −25.72 24.34 −.16 −6.46 20.74 −.05
Step 4 .10** .11**
 Parent years of education −0.06 0.51 −.02 0.93 0.43 .33*
 Group 8.09 1.87 .56** 3.56 1.59 .31*
 Follow-in comments 35.33 33.40 .22 46.34 28.38 .39
 Group × Follow-in Comments −105.66 42.32 −.47** −91.38 35.97 −.51**
Note.Parent years of education and follow-in comments were grand mean centered. Ratio values for follow-in comments were used to account for child engagement.
Note.Parent years of education and follow-in comments were grand mean centered. Ratio values for follow-in comments were used to account for child engagement.×
aPLS–4 Auditory Comprehension difference score.
aPLS–4 Auditory Comprehension difference score.×
bPLS–4 Expressive Communication difference score.
bPLS–4 Expressive Communication difference score.×
*p < .05. **p < .01.
*p < .05. **p < .01.×
TABLE 6 Results of multiple regression analyses predicting language gain scores.
Results of multiple regression analyses predicting language gain scores.×
Step Language outcomes
Language comprehensiona Language productionb
ΔR2 B SE B β ΔR2 B SE B β
Step 1 .00 .18**
 Parent years of education 0.22 0.58 .06 1.22 0.42 .43**
Step 2 .34** .09*
 Parent years of education 0.01 0.48 .00 1.14 0.40 .40**
 Group 8.48 1.93 .59** 3.55 1.62 .31*
Step 3 .02 .002
 Parent years of education 0.25 0.53 .07 1.20 0.45 .42**
 Group 7.91 2.00 .55** 3.41 1.70 .30*
 Follow-in comments −25.72 24.34 −.16 −6.46 20.74 −.05
Step 4 .10** .11**
 Parent years of education −0.06 0.51 −.02 0.93 0.43 .33*
 Group 8.09 1.87 .56** 3.56 1.59 .31*
 Follow-in comments 35.33 33.40 .22 46.34 28.38 .39
 Group × Follow-in Comments −105.66 42.32 −.47** −91.38 35.97 −.51**
Note.Parent years of education and follow-in comments were grand mean centered. Ratio values for follow-in comments were used to account for child engagement.
Note.Parent years of education and follow-in comments were grand mean centered. Ratio values for follow-in comments were used to account for child engagement.×
aPLS–4 Auditory Comprehension difference score.
aPLS–4 Auditory Comprehension difference score.×
bPLS–4 Expressive Communication difference score.
bPLS–4 Expressive Communication difference score.×
*p < .05. **p < .01.
*p < .05. **p < .01.×
×