Social Communication and Parent Verbal Responsiveness Across Interaction Contexts in Toddlers on the Autism Spectrum
Publication: American Journal of Speech-Language Pathology
Volume 33, Number 3
Pages 1266-1282
Abstract
Purpose:
Interactions with caregivers during the ordinary activities that occur as families go about their everyday lives are critical to supporting children's acquisition of social communication and language skills. The purpose of this study was to examine child communication and parent verbal responsiveness across interaction contexts in 211 children (Mage = 20 months) on the autism spectrum (n = 121), with developmental delay (n = 46), or with typical development (n = 44).
Method:
Families participated in up to eight activities during an hour-long, video-recorded home observation. We tested differences in the strength of associations between diagnostic group and interaction context using linear mixed-effects models, with child rate per minute of communication and proportions of parent follow-in comments and directives as outcome variables. Child communicative functions expressed across contexts were also examined.
Results:
Children across groups communicated at significantly higher rates per minute during book sharing and play with people compared to other interaction contexts. Most child communication was for the function of joint attention during book sharing, for social interaction during play with people, and for behavior regulation during necessary activities such as family chores and meals. On average, parents of children responded using proportionally more follow-in comments during book sharing and play compared to necessary activities, during which parents used more follow-in directives.
Conclusion:
Results provide a glimpse into the dyadic communication that may occur within everyday activities at home, which supports the need for future intervention research and may aid clinicians seeking to identify activities that serve as important contexts for intervention.
Interactions with caregivers during the ordinary activities that occur as families go about their everyday lives are critical to supporting the acquisition of social communication and language skills for children with and without developmental delays (DDs) and autism (Bernheimer & Weisner, 2007; Bottema-Beutel & Kim, 2021; Kuchirko & Tamis-LeMonda, 2019; Spagnola & Fiese, 2007). Therefore, parent-implemented early intervention (EI) models for children with DD and autism are delivered in the natural environment and have an ever-strengthening evidence base (Cheng et al., 2022; Heidlage et al., 2020; Wetherby et al., 2018). Within such models, speech-language pathologists (SLPs) and EI providers are charged with collaborating with families to choose everyday activities that align with their priorities and to learn how to embed intervention strategies to support their child's learning (American Speech-Language-Hearing Association [ASHA], n.d.; Division for Early Childhood [DEC], 2014). It is important to consider the potential influences of interaction context on parent verbal responsiveness (PVR) and child social communication and language development (Delehanty et al., 2023; Edmunds et al., 2019).
Important predictors of developmental outcomes have been identified in autistic children as well as those with DD and typical development (TD), including rate per minute of communication, inventory of communicative gestures, and the initiation of joint attention, as well as parental responsiveness to young children's focus of attention and communicative acts (Bottema-Beutel & Kim, 2021; Brady et al., 2004; Charman et al., 2005; Delehanty et al., 2023; Delehanty & Wetherby, 2021; Holme et al., 2022; Thurm et al., 2007). Still, limited research has explored whether child communication and PVR vary across interaction contexts for toddlers with DD and autism. This study is part of a series of studies designed to increase our understanding of the patterns of dynamic, transactional communication observed in the home environment between toddlers and their parents (Delehanty et al., 2023; Delehanty & Wetherby, 2021). Rates per minute of child communicative acts and proportions of communicative functions expressed, as well as patterns of PVR observed across the entire home observation for this sample, were reported by Delehanty and Wetherby (2021) and Delehanty et al. (2023), respectively. The current study builds on this previous work with a fine-grained examination of child communication and PVR across interaction contexts.
The Importance of Interaction Context
Everyday activities as interaction contexts have several unique characteristics that support child learning. First, these activities present repeated, built-in opportunities for social interaction and language learning (Kashinath et al., 2006). Next, they provide structure and predictability, increasing the likelihood that children will learn the words and phrases their caregivers use within that interaction (Spagnola & Fiese, 2007; Tamis-LeMonda et al., 2019). Finally, everyday activities allow families to meet their basic needs while engaging and teaching their child, decreasing the need for young children to “generalize” newly learned and developing skills because they are practicing them in the same settings in which they will use them (Schreibman et al., 2015). Thus, it is not surprising that an increased participation in everyday activities is positively correlated with child mental health and behavior and is also related to reduced parental stress in children with neurodevelopmental delays (Hatherly et al., 2022).
In a review of the evidence for EI practices for autistic children under the age of 3 years, Zwaigenbaum et al. (2015) emphasized the importance of active family involvement and family-centered intervention practices that respect the preferences and priorities of caregivers. A focus on building their capacity to provide learning opportunities during everyday activities in the environments in which the child spends time was also endorsed. These recommendations are consistent with Part C of the Individuals with Disabilities Education Improvement Act of 2004 (34 C.F.R. § 303.12(b)) and those of professional organizations (ASHA, n.d.; DEC, 2014). Through participation in EI that is implemented by parents across interaction contexts, active engagement is promoted, and children with autism and DD acquire meaningful skills (Dunst & Espe-Sherwindt, 2016; Schertz et al., 2011; Schertz & Horn, 2018; Woods & Brown, 2011; Woods et al., 2011). Moreover, caregivers themselves develop enhanced self-efficacy and increase their capacity to incorporate strategies during the hours in which an interventionist is not present (Wetherby et al., 2018).
Child Communication Across Interaction Contexts
A large body of published literature exists that has examined how contextual factors shape patterns of communication in young children with TD. These lines of research have focused on several possible influences including familiarity with the setting (e.g., Lewedag et al., 1994), conversation partner (e.g., Bornstein et al., 2000), and materials or topics (e.g., Cleave & Bird, 2006). Generally, findings suggest that children communicate more frequently and use increasingly sophisticated forms at home, when they are interacting with their mothers, and with familiar topics and materials in comparison to interactions in laboratory settings, speaking to researchers, and when the materials or topics are unfamiliar.
Fewer studies have compared child communication and language across different activity-based interaction contexts. Hoff (2010) examined these variables during book reading, mealtime, and toy play in toddlers with TD between the ages of 18 months and 3 years and found nonsignificant differences in the number of child utterances across contexts. However, increased vocabulary diversity and a larger number of topic-continuing utterances were noted during shared book reading relative to other contexts. More recently, Gros-Louis et al. (2016) reported that 12-month-old toddlers with TD used more speechlike syllable shapes during book reading compared to puppet and toy play. In a related study, Miller et al. (2017) observed that infants produced more directed vocalizations and gestures while playing with traditional toys such as nesting cups compared to electronic toys that provided feedback in the form of sounds or lights.
Only two known studies have investigated communicative functions expressed by toddlers with TD across interaction contexts. Wetherby and Rodriguez (1992) compared communication during a structured, clinician-directed context to an unstructured free-play setting in a small sample of 12- to 24-month-old children. Results indicated that children requested objects or actions significantly more often in the structured context but used a similar number of comments to direct the adult's attention to an object or event in both contexts. The second study examined the communicative functions expressed by 12-month-old toddlers during shared book sharing and toy play (Yont et al., 2003). Toddlers directed their mothers' attention to something in the environment outside the play setting and made comments about ongoing actions and events significantly more often during toy play than in book sharing. Alternatively, during book reading, toddlers more frequently commented on a joint focus to which both were already attending (Yont et al., 2003).
Research on patterns of communication and language across interaction contexts for autistic children and those with DD is even more limited. Most studies comparing the relationship between activity-based interaction context and communication skills of children with autism have focused on play. Binns et al. (2022), for instance, used observational coding methods to compare the social engagement of young autistic children (Mage = 42.5 months) during gross motor and symbolic play. Children spent more time engaged with caregivers in the gross motor play context relative to the symbolic play context, but also spent significantly more time unengaged with objects or people during gross motor play. Play with symbolic toys often resulted in children focusing more on objects than on caregivers. On average, the number of child utterances was statistically equivalent between contexts (Binns et al., 2022). These findings are in contrast to those of O'Brien and Bi (1995), who studied young children with DD and TD (Mage = 25 months) who were observed interacting with their teachers in a child care. Children included in this study spoke more often and used more complex language during symbolic play compared to gross motor play activities (O'Brien & Bi, 1995).
Only two known studies to date have examined child communication across interaction contexts that were designed to elicit distinct communicative functions. First, Kover et al. (2014) examined the use of comments and requests, as well as turns taken, in three contexts that included the Autism Diagnostic Observation Schedule (ADOS; Lord et al., 1999) and parent–child as well as examiner–child free-play, in a sample of 63 autistic children who were approximately 45 months of age. They found a slight advantage to both play-based contexts with regard to the frequency of all three types of child pragmatic language. Next, Özçalışkan et al. (2016) coded the gestures produced by young children with and without autism, matched on expressive vocabulary and observed in contexts that encouraged commenting and requesting. Children with autism (Mage = 30 months) used significantly fewer gestures than those with TD (Mage = 23 months) in both contexts. Variability in the production of deictic gestures across interaction contexts was related to later vocabulary in both groups.
Thus far, consistent with findings from studies constrained to one activity context, research indicates that autistic children evidence communication delays across interaction contexts compared to children with TD. However, very little research has focused on this topic for children with autism and DD. Additional inquiry is needed to increase the understanding of child communication across interaction contexts and to inform EI targets for these populations. Moreover, given the transactional nature of language development and the reciprocal influences of dyadic interactions between communication partners within and across contexts (McLean & Snyder-McLean, 1978; Sameroff, 1975, 2009), another important variable to consider is parent verbal responsiveness (PVR).
Parent Talk Across Interaction Contexts
For children with TD, variation in parent language use across interaction contexts has inspired comparatively more research than has the study of child communication. Holme et al. (2022) recently conducted a scoping review to map the literature on the amount and complexity of language used across interaction contexts for parents and children with TD aged 1–5 years. Most of the 59 included studies examined communication in toy play contexts, followed by shared book reading. The authors concluded that play appeared to promote a balance of conversational turns among parents and children, while book reading presented more opportunities for parents to embed complex language in the interaction. Results were mixed for mealtime and caregiving interaction contexts (e.g., Bornstein et al., 1999; Hoff, 2010; Tulviste, 2003), and only two studies included outdoor play (Cameron-Faulkner et al., 2018; Soderstrom & Wittebolle, 2013). Collectively, the available literature supported shared book reading and toy play as contexts in which parents could feasibly scaffold child language and communication development (Dowdall et al., 2020).
For children on the autism spectrum, results of three recent systematic reviews indicate that PVR that follows the child's focus of attention and adds linguistic information has significant associations with language learning and engagement state (Bottema-Beutel & Kim, 2021; Edmunds et al., 2019; Wan et al., 2019). PVR has also been shown to predict language skills in children with DD (Brady et al., 2004, 2014; Delehanty et al., 2023; McDuffie & Yoder, 2010). Three types of PVR that appear to be particularly important for promoting language outcomes include linguistic mapping (in which the parent provides a label for the word the child seems to be trying to say), expansions (whereby the parent repeats what the child said and adds words), and follow-in directives for language (when the parent invites the child to communicate about something they were focused on, asking a question, or requesting that the child imitate a model, for instance; Bottema-Beutel & Kim, 2021; Delehanty et al., 2023; Haebig et al., 2013; McDuffie & Yoder, 2010).
Given the observed differences in communication across interaction contexts for children with TD and their parents, context is likely an important factor when considering language development, as well as intervention setting, for autistic children and those with DD. However, studies of parent talk in these populations across different interaction contexts are limited. Studies of PVR included in the reviews by Bottema-Beutel and Kim (2021) and Wan et al. (2019) were limited to a single interaction context (i.e., play). The exceptions were investigations that analyzed automated, daylong recordings; however, activity contexts and activity-oriented communication in those studies were difficult to discern and analyze (Bottema-Beutel & Kim, 2021). The limitations of the current literature make it difficult to directly compare patterns of PVR across interaction contexts for young children with TD, DD, and autism. Accordingly, these findings led the authors of these reviews to recommend research that characterizes PVR in natural, dynamic social contexts that include a range of family activities (e.g., Tamis-LeMonda et al., 2019).
Studies that examine patterns of child communication and PVR across different interaction contexts will deepen understanding of how parents and children with DD and those on the autism spectrum communicate in the natural environment and what aspects of interaction context may influence the behaviors of young children and their caregivers. Certain contexts may offer more opportunities for caregivers to scaffold and enhance the frequency and quality of child language. Other activities may allow children opportunities to express a variety of functions, such as making requests or initiating joint attention to share enjoyment in events and actions. Furthermore, by examining communicative interactions across everyday activities, SLPs and EI providers will be better equipped to follow recommended practices, which emphasize the importance of using family activities as intervention contexts for young children with disabilities (ASHA, n.d.; DEC, 2014).
Purpose of This Study
The purpose of this study was to examine patterns of child communication and PVR across interaction contexts during an hour-long, video-recorded home observation in toddlers later identified with autism, DD, and TD. This study was guided by four aims. First, we examined the proportions of time families spent in different contexts across diagnostic groups, with the goals of providing information about their preferences and aiding in the interpretation of results of other aims. Our second aim was to compare mean rates per minute of child communication across interaction contexts, to augment the limited research base in this area. Third, we examined proportions of child communicative functions expressed within interaction contexts. Many assessments of young children's communication and language focus on the form of the communicative act. However, studying the functions expressed by those forms is vital to understanding the full range of young children's communicative capabilities. Finally, our fourth aim, in response to recommendations from recent reviews (Bottema-Beutel & Kim, 2021; Edmunds et al., 2019; Wan et al., 2019), was to explore patterns of PVR across interaction contexts.
Method
Participants
Participants were 211 toddlers on the autism spectrum (n = 121), with DD (n = 46), or with TD (n = 44) recruited through screening in primary care and evaluated by the FIRST WORDS Project (Wetherby et al., 2008). To be included in the current study, children completed the Communication and Symbolic Behavior Scales (CSBS) Behavior Sample and an hour-long, video-recorded home observation (M = 56.1 min, SD = 6.3) in the second year of life (Mage = 20.3 months, SD = 2.0). Children did not differ on chronological age across groups, F(2, 208) = 0.37, p = .69. The 18- to 24-month age window was chosen because it is at this age that (a) the American Academy of Pediatrics recommends screening for autism in primary care (Hyman et al., 2020), (b) a stable diagnosis of autism may be made (Guthrie et al., 2013), and (c) children are often referred for an evaluation to determine eligibility for EI.
A developmental evaluation was subsequently conducted at 36.6 months (SD = 4.8), at which time a clinical best estimate diagnosis of TD, DD, or autism spectrum disorder was made by a team of experienced diagnosticians. Children identified as having developmental delays received a T score that was at least 1.25 SDs below the mean on any subscale of the Mullen Scales of Early Learning (MSEL; Mullen, 1995), and autism was ruled out following a diagnostic battery that also included the ADOS and the Vineland Adaptive Behavior Scales–Second Edition (Sparrow et al., 2005). Children were classified as typically developing if all MSEL T scores were within 1 SD of the mean and the team identified no concern about autism symptoms. Children on the autism spectrum were assigned a clinical estimate diagnosis of autism spectrum disorder using all available information obtained during the diagnostic evaluation (American Psychiatric Association [APA], 2013).
Participant demographic and developmental information for this sample was previously published (Delehanty & Wetherby, 2021) and is included for reference in Supplemental Materials S1 and S2, respectively. To summarize, 81% of the children were male. Sixty-eight percent of parents identified their child as White, 20% were Black, 10% were of more than one race, and 2% were Asian. Eight percent of children were Hispanic. A higher proportion of children in the DD group was Black compared to the other groups, χ2(8, N = 211) = 24.93, p < .01. Twenty-three percent of mothers graduated from high school, 22% were college graduates, and 27% completed a graduate degree. Thirty-one percent of fathers completed high school, 17% were college graduates, and 23% completed a graduate degree. A larger proportion of parents in the TD group had a graduate degree, χ2(12, N = 211) = 27.06, p < .01. Mothers were 31 years old, and fathers were 33 years old, on average, at the time of their child's birth. Mothers of children in the DD group were significantly younger than those of children in the TD group, F(2, 205) = 3.24, p < .05. Parents gave written informed consent for their participation. This study was approved by the institutional review board at Florida State University.
Procedure
Each video-recorded home observation was collected to provide information about child communication, social interaction, and play in the natural environment. Interaction contexts, child communicative acts, and PVR were coded using Noldus Pro Observer XT software.
Observational Coding Scheme
Interaction context. During the home observation, families were asked to participate in activities from up to eight categories. Four interaction contexts represented activities that focused on book sharing and play: (a) book sharing, (b) play with people (dyadic play without objects, including social games such as peekaboo and “I'm gonna get you,” as well as songs and rhymes like The Wheels on the Bus and Itsy Bitsy Spider), (c) play with toys, and (d) play with large objects as props (e.g., swing set, ride-on toy). The remaining four included necessary activities that families engage in every day: (e) caregiving (e.g., getting dressed, washing hands), (f) family chores (e.g., feeding a pet, checking the mail), (g) meals or snacks, and (h) transitions between activities. Home observations were recorded at an optimal time of day chosen by families. Recordings were taken by project staff members who were unaware of child diagnostic group and not involved in the administration of assessment measures. Families received information about the home observation and a set of written, standardized instructions in advance of the video recording. To ensure that the observation was as naturalistic as possible, they were asked to participate in as many activities as they could but were not instructed to complete a certain number or in any particular order.
Child communicative acts and communicative functions. Child communicative acts were identified using criteria from the CSBS Developmental Profile (Wetherby & Prizant, 2002) as behaviors that (a) included a gesture, sound, word, or word combinations; (b) were directed toward another person; and (c) expressed a communicative function. We assigned one of four communicative functions to each communicative act (Bruner, 1981), including (a) behavior regulation: requesting or protesting actions and entities; (b) social interaction: greeting, “showing off,” or otherwise drawing attention to oneself; (c) joint attention: directing attention toward an entity or event to share interest or enjoyment, comment, or request information; or (d) unclear.
PVR. In the second wave of observational coding, we examined the 3 s after each child communicative act for the occurrence of a contingent parent verbal response, which was coded as synchronous or asynchronous dependent upon whether the PVR followed the child's focus of attention (Delehanty et al., 2023). Modifiers to synchronous PVR included (a) follow-in verbal comments, which provided additional semantic or syntactic information to the child's utterance but did not ask that the child change their actions; (b) follow-in directives, in which the parent directed the child to say or do something that mapped onto the object or event they were currently focusing on; or (c) follow-in nonverbal comments, which were defined as affirmative responses that did not add linguistic information to the child's communicative act (e.g., “Mm-hm,” “Oh,” providing sound effects, etc.; McDuffie & Yoder, 2010). Asynchronous responses refocused the child's attention or behavior and were coded as comments or directives. Finally, if the parent did not respond within 3 s or spoke to another person in the room instead, this was coded as a missed opportunity. If the parent's response was inaudible, it was considered uncodeable (M = 1% of all PVR, SD = 4).
Observational Coders and Interrater Reliability
Coders were two trained undergraduate research assistants naive to the child diagnostic group and study aims. Interrater reliability was assessed using Cohen's kappa coefficients (κ; Cohen, 1960). Coding of interaction context was evaluated in terms of duration and sequence of intervals, measured in minutes and seconds, for which the onset of one was the offset of another. Contexts were assigned based upon the activity the parent was attempting to engage the child in. At the start of each observation, transition was assigned as the default category. Coders shifted from transition once the first activity became apparent. If the parent briefly shifted between interaction contexts, coders did not assign a new context. If the parent shifted for a minimum of 1 min, coders returned to the time point of the switch to code the onset of the new context (Wetherby et al., 2016). Intervals were visualized within Observer XT, and disagreements were resolved through consensus. Fifty (24%) videos were double-coded. The resulting mean κ = .78, 95% confidence interval (CI) [.76, .79], indicated acceptable agreement (Landis & Koch, 1977; McHugh, 2012). Interrater reliability for identification of child communicative acts by type and function (κ = .80–.84) and PVR type (κ = .77, 95% CI [.76, .78]) was also acceptable (Delehanty et al., 2023; Delehanty & Wetherby, 2021).
Analytic Plan
To meet our first goal, we compared average proportions of time spent in different contexts across groups (autism, DD, and TD) using one-way analysis of variance (ANOVA). Cases were excluded by analysis rather than listwise, as ns varied based upon the number of families engaging in each activity. The number of parent–child dyads who engaged in each interaction context at least once during the home observation (N = 211) was as follows: book sharing (n = 161), play with people (n = 171), play with toys (n = 209), play with props (n = 105), caregiving (n = 169), chores (n = 133), meals/snacks (n = 187), and transition (N = 211). Although different numbers of participants engaged in different interaction contexts, the proportions of parent–child dyads who participated in each context on at least one occasion during their home observation did not differ between diagnostic groups, with one exception (all ps < .09; see Supplemental Material S3). A significantly smaller proportion of families with children on the autism spectrum than those with TD participated in family chores, F(2, 208) = 5.03, p < .01. To conservatively control for violations of the assumption of homogeneity of variance that may occur with unequal sample sizes and the large number of planned post hoc comparisons, the Bonferroni correction was applied. Hedges's g was calculated and interpreted using the following conventions for effect sizes: 0.20 = small, 0.50 = medium, and 0.80 = large (Cohen, 1988).
To address our second aim, we tested differences in the strength of association between diagnostic group and interaction context using a simple linear mixed-effects model (LMM) with child rate per minute of communication as the outcome variable (Brauer & Curtin, 2018). LMM is a flexible method that increases the rigor in modeling repeated-measures data and the power to detect associations of interest based on the inclusion of participants with missing data points in the analysis (Harel & McAllister, 2019; Walker et al., 2019). We compared rate of communication with participant as a random effect and diagnostic group, interaction context, and the interaction of group and context as fixed effects. Post hoc multiple comparisons for significant fixed effects were conducted on estimates using paired-samples t tests with the Bonferroni correction applied to minimize Type I error. As mentioned, rates of communication across diagnostic groups were previously reported (Delehanty & Wetherby, 2021); however, this term was included in the LMM to explore the potential interaction between group and interaction context on rate of communication. Where interaction terms were not statistically significant, we chose to report the original model parameters rather than respecifying, in order to address our original research aim that included exploration of an interaction between child communication and diagnostic group.
For our third aim, we examined the proportions of child communicative functions expressed across interaction contexts for the entire sample. A repeated-measures ANOVA was employed to maximize the use of all available dependent data given the differing numbers of parent–child dyads who participated in each activity as well as the heterogeneous patterns of child communication we observed. Again, pairwise comparisons were corrected (Bonferroni) and examined. Partial eta squared (ηp2) was reported as a measure of effect size, with values of .01 interpreted as a small effect; .06, as a medium effect; and .14, as a large effect (Cohen, 1988).
Finally, in constructing our approach to Aim 4, we considered the number of parents who responded using specific PVR types within interaction contexts, in addition to the unbalanced number of families who participated in each context. We determined that our power to interpret the effects of a model that examined the eight contexts separately was diminished. Therefore, we combined PVR that occurred during book sharing and the three types of play into one category, termed book sharing and play, and combined PVR during caregiving, family chores, meals/snacks, and transitions into a second category, termed necessary activities. A set of three LMMs was employed to test differences in the strengths of associations between group and interaction context, with mean proportions of PVR types as the outcome variables (i.e., parental follow-in verbal comments, follow-in directives, and follow-in nonverbal comments). We compared PVR with group, interaction context, and the interaction of group and context as fixed effects. Again, post hoc multiple comparisons for significant fixed effects in each model were controlled for with the Bonferroni correction. These analyses were treated as exploratory, and results were interpreted with caution, given unequal sample sizes participating and using specific PVR types in different interaction contexts. SPSS v.27 was used for all analyses.
Results
Time Spent in Interaction Contexts
Children and families who participated in this study, across diagnostic groups, were observed to spend most of their home observation engaged in play with toys (M = 39%, SD = 9), followed by meals and snacks (M = 16%, SD = 12; see Table 1). On average, parents of children in the TD group spent significantly more time in book sharing and family chores than those of autistic children, F(2, 208) = 5.06, p < .01, and F(2, 208) = 9.01, p < .001, respectively. Parents of children on the autism spectrum spent more time in transition than parents of children in the DD and TD groups, F(2, 208) = 8.54, p < .001.
| Percentage of time | Autism | DD | TD | df | F | Effect size (Hedges's g)c of group differences | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| (n = 121) | (n = 46) | (n = 44) | |||||||||
| M | SD | M | SD | M | SD | Autism–DD | Autism–TD | DD–TD | |||
| Book sharing | 8.6a | 8.0 | 10.1a,b | 8.7 | 13.4b | 9.9 | 2, 158 | 5.06** | 0.18 | 0.56 | 0.35 |
| Play with people | 8.7 | 9.5 | 8.6 | 7.7 | 7.8 | 7.5 | 2, 168 | 0.19 | 0.01 | 0.10 | 0.11 |
| Play with toys | 40.6 | 19.9 | 36.4 | 17.9 | 35.3 | 18.1 | 2, 206 | 1.66 | 0.22 | 0.27 | 0.06 |
| Play with props | 6.0 | 9.6 | 7.6 | 12.9 | 4.0 | 7.7 | 2, 102 | 1.51 | 0.15 | 0.22 | 0.34 |
| Caregiving | 8.0 | 7.7 | 10.3 | 9.0 | 8.7 | 7.1 | 2, 166 | 1.42 | 0.27 | 0.09 | 0.20 |
| Chores | 4.8a | 6.7 | 7.1a,b | 8.6 | 10.5b | 9.0 | 2, 130 | 9.01*** | 0.31 | 0.77 | 0.39 |
| Meals and snacks | 15.0 | 12.3 | 16.4 | 10.0 | 19.2 | 12.4 | 2, 184 | 2.01 | 0.12 | 0.34 | 0.25 |
| Transition | 8.3a | 13.3 | 3.5b | 4.6 | 1.3b | 3.7 | 2, 208 | 8.54*** | 0.41 | 0.61 | 0.53 |
Note. Number of parent–child dyads who engaged in each interaction context during the home observation (N = 211): book sharing (n = 161), caregiving (n = 169), chores (n = 133), meals/snacks (n = 187), play with people (n = 171), play with toys (n = 209), play with props (n = 105), and transition (N = 211). DD = developmental delay without autism; TD = typical development.
a,b
Means in the same row with different superscripts differ significantly at p < .05, derived using analysis of variance with multiple comparisons (Bonferroni correction).
c
Hedges's g: .20 = small effect; .50 = medium effect; .80 = large effect (Cohen, 1988).
**
p < .01.
***
p < .001.
Rate Per Minute of Child Communication
Descriptive statistics and results of the LMM comparing child communication across interaction contexts are displayed in Tables 2 and 3, respectively. Main effects of diagnostic group, F(2, 228.61) = 31.30, p < .001, and context, F(7, 219.96) = 23.90, p < .001, were significant, while the interaction term was not, F(14, 207.70) = 1.74, p = .05. Across contexts, model estimates indicated that children in the TD group communicated at significantly higher rates than autistic children and those with DD (autism–TD mean difference ± SE = 2.02 ± .26, p < .001, 95% CI [1.40, 2.63]; DD–TD = 1.47 ± .31, p < .001, 95% CI [0.74, 2.21; autism–DD = −0.55 ± .25, p = .09, 95% CI [−1.15, 0.06]).
| Rate per minute | Autism | DD | TD | |||
|---|---|---|---|---|---|---|
| (n = 121) | (n = 46) | (n = 44) | ||||
| M | SD | M | SD | M | SD | |
| Overall rate per minutea | 2.7 | 1.5 | 3.5 | 1.5 | 5.2 | 1.4 |
| Interaction context | ||||||
| Book sharing | 3.7 | 2.6 | 4.2 | 2.5 | 6.5 | 3.0 |
| Play with people | 4.1 | 2.3 | 4.7 | 2.5 | 5.8 | 2.1 |
| Play with toys | 2.6 | 1.6 | 3.6 | 1.7 | 5.2 | 1.8 |
| Play with props | 2.8 | 2.3 | 3.0 | 1.4 | 3.8 | 1.6 |
| Caregiving | 3.1 | 1.8 | 3.4 | 1.7 | 4.9 | 2.0 |
| Chores | 2.8 | 2.5 | 3.4 | 2.3 | 4.5 | 2.1 |
| Meals and snacks | 2.5 | 1.7 | 3.2 | 1.8 | 5.1 | 2.0 |
| Transition | 1.4 | 1.9 | 1.8 | 1.2 | 3.3 | 2.2 |
Note. Number of parent–child dyads who engaged in each interaction context during the home observation (N = 211): book sharing (n = 161), caregiving (n = 169), chores (n = 133), meals/snacks (n = 187), play with people (n = 171), play with toys (n = 209), play with props (n = 105), and transition (N = 211). DD = developmental delay without autism spectrum disorder; TD = typical development.
a
Overall rate of communication is provided for reference and was reported in the work of Delehanty and Wetherby (2021).
| Fixed effect | Estimate | SE | 95% CI | t | p |
|---|---|---|---|---|---|
| Child rate per minute of communication | |||||
| Intercept | 3.269 | .452 | [2.375, 4.164] | 7.24 | < .001 |
| Group: autism | −1.821 | .495 | [−2.800, −0.842] | −3.68 | < .001 |
| Group: DD | −1.422 | .113 | [−0.391, 0.058] | −1.47 | .015 |
| Context: book sharing | 3.211 | .540 | [2.146, 4.276] | 5.95 | < .001 |
| Context: play with people | 2.540 | .510 | [1.534, 3.545] | 4.98 | < .001 |
| Context: play with toys | 1.886 | .441 | [1.013, 2.759] | 4.28 | < .001 |
| Context: play with props | 0.540 | .566 | [−0.577, 1.656] | 0.95 | .342 |
| Context: caregiving | 1.682 | .464 | [0.766, 2.599] | 3.63 | < .001 |
| Context: chores | 1.204 | .499 | [0.219, 2.190] | 2.41 | .017 |
| Context: meals & snacks | 1.884 | .466 | [0.962, 2.805] | 4.04 | < .001 |
| Interaction Context × Group | |||||
| Book Sharing × Autism | −0.950 | .612 | [−2.157, 0.257] | −1.55 | .122 |
| Play With People × Autism | 0.076 | .567 | [−1.043, 1.194] | 0.13 | .894 |
| Play With Toys × Autism | −0.721 | .481 | [−1.674, 0.232] | −1.50 | .137 |
| Play With Props × Autism | 0.784 | .624 | [−0.447, 2.015] | 1.26 | .210 |
| Caregiving × Autism | −0.073 | .511 | [−1.084, 0.937] | −0.14 | .886 |
| Chores × Autism | 0.119 | .572 | [−1.010, 1.248] | 0.21 | .835 |
| Meals/Snacks × Autism | −0.817 | .511 | [−1.828, 0.194] | −1.60 | .112 |
| Book Sharing × DD | −0.887 | .728 | [−2.321, 0.547] | −1.22 | .224 |
| Play With People × DD | 0.302 | .660 | [−1.001, 1.604] | 0.46 | .648 |
| Play With Toys × DD | −0.149 | .559 | [−1.256, 0.959] | −0.27 | .791 |
| Play With Props × DD | 0.651 | .728 | [−0.787, 2.087] | 0.89 | .373 |
| Caregiving × DD | −0.133 | .591 | [−1.301, 1.035] | −0.23 | .822 |
| Chores × DD | 0.307 | .658 | [−0.991, 1.605] | 0.47 | .641 |
| Meals/Snacks × DD | −0.506 | .594 | [−1.679, 0.668] | −0.85 | .396 |
Note. For all models, typical development served as the reference variable for group, and transition served as the reference variable for interaction context. CI = confidence interval; DD = developmental delay.
For the entire sample, on average, children communicated at significantly higher rates per minute during book sharing and play with people compared to all other interaction contexts (all ps < .001). Rates of communication during book sharing and play with people did not differ (mean difference ± SE = −0.7 ± .24, p = 1.00, 95% CI [−0.83, 0.70]). In contrast, children communicated at significantly lower rates during transitions between activities than all other interaction contexts except play with props (all other ps < .05). Rates of communication among the contexts of caregiving, chores, meals and snacks, play with props, and play with toys did not differ significantly for children in this sample (all ps > .18).
Communicative Functions Expressed
Average proportions of communicative functions used during interaction contexts for the entire sample are shown in Figure 1. Descriptive statistics and results of planned contrasts within contexts are displayed in Table 4. Communicative acts for all three functions were represented in each interaction context. The effect of communicative function was significant within each of the eight interaction contexts examined. Notably, more than half of all communicative acts were for behavior regulation during caregiving, family chores, meals and snacks, as well as transitions between activities. Proportions of communicative acts for this function were significantly larger than those for social interaction and joint attention in each of these contexts (see Table 4; all ps < .001). Play with toys followed a similar trend, with proportionally higher child communicative acts for behavior regulation (42%) compared to the other two functions, F(2, 205) = 36.93, p < .001, ηp2 = .27. Fifty-nine percent of acts for social interaction occurred during play with people, which was significantly larger than proportions of communication for behavior regulation (27%) and joint attention (13%), F(2, 167) = 115.84, p < .001, ηp2 = .58. Finally, 53% of child communication during book sharing was for joint attention, which was significantly more than both behavior regulation and social interaction, F(2, 154) = 150.46, p < .001, ηp2 = .66.
| Interaction context | Communicative function | F | df | p | ηp2 | Post hoc pairwise comparisons (Bonferroni p < .05) | ||
|---|---|---|---|---|---|---|---|---|
| Behavior regulation M (SD) | Social interaction M (SD) | Joint attention M (SD) | ||||||
| Book sharing (n = 156) | .37 (.29) | .10 (.17) | .53 (.30) | 150.46 | 2, 154 | < .001 | .66 | JA > BR > SI |
| Play with people (n = 169) | .27 (.21) | .59 (.26) | .13 (.18) | 115.84 | 2, 167 | < .001 | .58 | SI > BR > JA |
| Play with toys (n = 207) | .42 (.20) | .23 (.17) | .35 (.20) | 36.93 | 2, 205 | < .001 | .27 | BR > JA > SI |
| Play with props (n = 100) | .39 (.27) | .34 (.29) | .27 (.25) | 3.77 | 2, 98 | .026 | .07 | BR > JA |
| Caregiving (n = 160) | .57 (.29) | .22 (.23) | .21 (.22) | 56.81 | 2, 158 | < .001 | .42 | BR > SI, JA |
| Chores (n = 125) | .54 (.30) | .18 (.21) | .28 (.22) | 36.89 | 2, 123 | < .001 | .38 | BR > JA > SI |
| Meals & snacks (n = 184) | .57 (.26) | .23 (.23) | .19 (.18) | 90.08 | 2, 182 | < .001 | .50 | BR > SI, JA |
| Transition (n = 103) | .56 (.33) | .23 (.29) | .21 (.25) | 25.88 | 2, 101 | < .001 | .34 | BR > SI, JA |
Note. Proportions represent total count/all communicative functions expressed for each interaction context. Results were derived using repeated-measures analysis of variance with multiple comparisons (paired t tests with Bonferroni correction). Different participants' data are included in each analysis due to the unbalanced design. ηp2: .01 = small effect; .06 = medium effect; .14 = large effect (Cohen, 1988). JA = joint attention; BR = behavior regulation; SI = social interaction.
PVR
Descriptive statistics for PVR to child communication across interaction contexts for the entire sample are presented in Table 5 and by diagnostic group in Supplemental Material S4. All PVR types were represented in each interaction context. Parents responded with follow-in verbal comments 20% or less of the time in all activities except for book sharing (30%). Approximately 40% of PVR during chores and 36% of PVR during transitions were follow-in directives. Follow-in nonverbal comments accounted for about 56% of PVR during play with people.
| Proportion | Parent verbal response | |||
|---|---|---|---|---|
| Follow-in verbal comment | Follow-in directive | Follow-in nonverbal comment | Asynchronous or missed opportunity | |
| Overall | .19 (.12) | .32 (.12) | .37 (.15) | .12 (.19) |
| Interaction context | ||||
| Book sharing and play | .20 (.13) | .31 (.12) | .39 (.17) | .10 (.15) |
| Book sharing | .30 (.20) | .28 (.17) | .33 (.22) | .09 (.17) |
| Play with people | .10 (.12) | .27 (.19) | .56 (.24) | .07 (.12) |
| Play with toys | .20 (.15) | .33 (.15) | .37 (.18) | .10 (.12) |
| Play with props | .18 (.21) | .33 (.21) | .36 (.25) | .14 (.20) |
| Necessary activities | .17 (.15) | .35 (.17) | .34 (.18) | .15 (.17) |
| Caregiving | .15 (.15) | .37 (.21) | .35 (.24) | .13 (.19) |
| Chores | .17 (.17) | .40 (.22) | .30 (.21) | .14 (.17) |
| Meals and snacks | .18 (.16) | .33 (.20) | .37 (.20) | .12 (.16) |
| Transition | .17 (.23) | .36 (.30) | .27 (.29) | .19 (.26) |
Note. Proportions represent total count/all parent verbal responses. Number of parent–child dyads who engaged in each interaction context during the home observation (N = 211): book sharing (n = 158), caregiving (n = 164), chores (n = 126), meals/snacks (n = 184), play with people (n = 170), play with toys (n = 209), play with props (n = 101), and transition (n = 82).
Results of the three LMMs comparing PVR across two contexts (i.e., book sharing/play and necessary activities) are presented in Table 6. For the model comparing parents' use of follow-in verbal comments, main effects of group and interaction context were statistically significant, F(2, 208.06) = 12.83, p < .001, and F(1, 204.24) = 7.25, p < .01, respectively. The interaction term was nonsignificant, F(2, 204.27) = 1.01, p = .37. Across interaction contexts, parents of children with TD responded using proportionally more follow-in verbal comments than those of autistic children and children with DD (TD–autism mean difference ± SE = .10 ± .02, p < .001, 95% CI [.05, .15]; TD–DD = .11 ± .03, p < .001, 95% CI [.05, .18]). Parents of autistic children and those with DD did not differ in their use of follow-in verbal comments (mean difference ± SE = .01 ± .02, p = 1.00, 95% CI [.04, .06]). On average, parents of children in all groups responded using proportionally more follow-in verbal comments during book sharing/play compared to necessary activities (mean difference ± SE = .03 ± .01, p = .008, 95% CI [.01, .04]).
| Fixed effect | Estimate | SE | 95% CI | t | p |
|---|---|---|---|---|---|
| Parent verbal response type: follow-in verbal comments | |||||
| Intercept | .266 | .022 | [.223, .309] | 12.15 | < .001 |
| Group: autism | −.109 | .026 | [−.159, −.058] | −4.24 | < .001 |
| Group: DD | −.132 | .030 | [−.192, −.072] | −4.34 | < .001 |
| Context: book sharing/play | .025 | .018 | [.008, .039] | 3.05 | < .01 |
| Interaction Context × Group | |||||
| Book Sharing/Play × Autism | .015 | .022 | [−.028, .058] | 0.689 | .492 |
| Book Sharing/Play × DD | .036 | .026 | [−.015, .087] | 1.40 | .162 |
| Parent verbal response type: follow-in verbal directives | |||||
| Intercept | .362 | .024 | [.314, .410] | 14.89 | < .001 |
| Group: autism | −.009 | .028 | [−.065, .047] | −0.33 | .744 |
| Group: DD | −.026 | .034 | [−.092, .040] | −0.77 | .441 |
| Context: book sharing/play | −.033 | .022 | [−.053, −.021] | −4.54 | < .001 |
| Interaction Context × Group | |||||
| Book Sharing/Play × Autism | −.003 | .025 | [−.053, .047] | −0.12 | .906 |
| Book Sharing/Play × DD | −.014 | .030 | [−.073, .045] | −0.47 | .636 |
| Parent verbal response type: follow-in nonverbal comments | |||||
| Intercept | .285 | .027 | [.232, .337] | 10.70 | < .001 |
| Group: autism | .064 | .031 | [.003, .126] | 2.07 | .040 |
| Group: DD | .091 | .037 | [.018, .164] | 2.46 | .015 |
| Context: book sharing/play | .051 | .023 | [.006, .095] | 2.24 | .026 |
| Interaction Context × Group | |||||
| Book Sharing/Play × Autism | .006 | .026 | [−.046, .058] | 0.22 | .830 |
| Book Sharing/Play × DD | −.008 | .031 | [−.070, .053] | −0.28 | .783 |
Note. For all models, typical development served as the reference variable for group, and necessary activities served as the reference variable for context. CI = confidence interval; DD = developmental delay.
Turning to follow-in directives, the main effect of interaction context was significant, F(1, 216.60) = 12.96, p < .001. The main effect of group and the interaction term were nonsignificant, F(2, 225.30) = 0.90, p = .41, and F(2, 216.63) = 0.14, p = .87, respectively. Parents of children in all diagnostic groups, on average, responded using proportionally more follow-in directives during necessary activities than during book sharing and play (mean difference ± SE = .04 ± .01, p < .001, 95% CI [.02, .06]).
Finally, regarding follow-in nonverbal comments, significant main effects for group and interaction context were observed, with the interaction term remaining nonsignificant, group: F(2, 208.64) = 4.10, p = .018; context: F(1, 204.95) = 18.94, p < .001. Parents of children on the autism spectrum and those with DD used follow-in nonverbal comments more often than those of children with TD (autism–TD mean difference ± SE = .07 ± .03, p = .044, 95% CI [.01, .13]; DD–TD = .09 ± .03, p = .025, 95% CI [.01, .17]). Parents of children across groups also used follow-in nonverbal comments significantly more often during book sharing/play than during necessary activities (mean difference ± SE = .05 ± .01, p < .001, 95% CI [.02, .07]).
Discussion
Time Spent in Interaction Contexts
During the 1-hr, video-recorded home observations analyzed in this study, we found that toddlers and their caregivers spent about half of the time engaged in play with toys, play with people, and play with props. Play makes up only a small portion of a typical day for families of young children; however, it appeared to be a natural activity for a home observation. In this study, parents of children in the TD group spent significantly larger proportions of time in book sharing and family chores than did families of children on the autism spectrum. One possible reason for this difference may be that some autistic children in the sample did not sustain shared attention and engagement as long as children with TD during these activities. On the other hand, the differences may have been related to parents' predilections or motivations. Parents of autistic children may have anticipated that their children might have additional support needs in these contexts and either did not include or abbreviated these activities (Boyd et al., 2014). Studies of book sharing in preschool-aged children have identified differences in engagement between autistic children and those with TD, finding that children on the autism spectrum spend significantly more time in non-engaged states and have lower rates of verbal participation (Fleury & Hugh, 2018; Fleury & Schwartz, 2017). Our finding of reduced time in this interaction context among families of toddlers with autism aligns with those findings.
All three groups spent a relatively small proportion of time in family chores. Some chores may happen frequently throughout the week but are short in duration (e.g., cleaning the table), therefore explaining the overall low proportion of time we observed. On the other hand, preparing a family chore for their home observation may have been more effortful for families than setting up a play context, particularly if families were unaccustomed to involving their toddler in this type of activity. Finally, it was not surprising to find that families of children on the autism spectrum, on average, spent proportionally more time than those of children with TD and DD in transitions between activities. Transitions can take longer for autistic individuals, who may strongly adhere to routines and prefer to remain in an activity once it has begun (APA, 2013; Boyd et al., 2014).
Child Communication Across Interaction Contexts
In examining the frequency of child communicative acts, we found that average rates per minute of communication during book reading and play with people were significantly higher than during other interaction contexts for the entire sample. Despite spending proportionally less time in book sharing than children with TD and results of extant research in this area (Fleury & Hugh, 2018; Fleury & Schwartz, 2017), it was encouraging to note that children on the autism spectrum and children with DD communicated at relatively high rates in this context. This finding was demonstrated for children in all three diagnostic groups and agrees with research thus far including children with TD (Gros-Louis et al., 2016; Hoff, 2010). In contrast, rates of communication across groups were significantly lower during transitions relative to those in which planned activities were more clearly transpiring. This finding aligns with studies that have reported more child communication during familiar, predictable interaction contexts (e.g., Bornstein et al., 2000; Cleave & Bird, 2006; Lewedag et al., 1994). Interestingly, although lower rates per minute of communication were observed in autistic children and those with DD relative to children with TD overall, the nonsignificant interaction term in this model indicated that patterns observed across contexts were not dependent on group membership.
There is limited research available that focuses specifically on play with people, but the high rates of child communication we observed in this context make conceptual sense. Play with people is often identified as recommended activity for intervention for autistic toddlers and those with DD as a high-energy context that supports shared enjoyment and social connection (Schreibman et al., 2015; Weitzman, 2013). Furthermore, the dyadic nature of play with people gives rise to fewer demands that children shift their attention between objects and communication partners (Adamson, 2018; Ross & Lollis, 1987), skills that are often delayed in autistic toddlers as well as toddlers with DD (Delehanty et al., 2018; Slonims & McConachie, 2006). As mentioned, we found that toy play appeared to be a preferred activity for all families. When conducting a screening or communication evaluation in a home-based setting, it may be useful for SLPs and EI providers to contrast rate of communication during toy play with rate during play with people. Differences may be particularly apparent when children are engaging in dyadic versus triadic coordination of attention with objects and communication partners.
Child Communicative Functions
Examining the proportions of communicative functions children expressed across interaction contexts, there were some activities that appeared to lend themselves, by their structure, to promoting one function over another. For example, over half of child communication during caregiving, family chores, meals and snacks, and transitions was for behavior regulation, when children were making choices, requesting, or refusing. In contrast, a large proportion of child communicative acts during book sharing were expressed for the function of joint attention, as children tapped or labeled pictures to draw the focus of their caregivers. Finally, communicative acts for the function of social interaction occurred frequently during play with people, when objects were not present and social exchanges were being shared dyadically between the adult and the child.
Considering the relatively large proportions of communication for behavior regulation that we observed across most activities, it is important to bear in mind that individuals on the autism spectrum may communicate more easily to make requests and protest than to initiate joint attention and social interaction. DDs in the areas of initiating and responding to joint attention have long been observed in autistic individuals, and joint attention has been found to be an important predictor of later language skills (APA, 2013; Franchini et al., 2019). However, it was of interest to note that the three functions, which are all important and needed, were represented across contexts. Our findings suggest that parents and interventionists may not need to work as hard to target certain communicative functions in some contexts. For example, knowing that many opportunities for joint attention exist during book sharing, parents could scaffold communication for behavior regulation as children select books, ask to turn the page, or request a favorite excerpt again. When there is space and time during necessary activities, parents may be encouraged to initiate joint attention by talking about objects, people, and events, while also fostering self-advocacy in the form of behavior regulation.
PVR
Our final goal was to explore patterns of PVR across interaction contexts. Consistent with the results of our previous aims, we observed that parents used a variety of responsive and directive communication that “followed in” to their child's focus of attention. Across PVR types, the joint effect of diagnostic group and interaction context (i.e., the interaction effect) was not statistically higher than the sum of both effects individually. Across diagnostic groups, the book sharing/play context was associated with higher proportions of parental follow-in verbal and nonverbal comments compared to necessary activities, which were associated with proportionally more follow-in directives. Parental use of both follow-in verbal comments and follow-in directives has been found to be related to language development in children with and without autism and DD (Delehanty et al., 2023; Haebig et al., 2013; McDuffie & Yoder, 2010). Additionally, parental responsiveness to a child's focus of attention, as well as to communicative initiations, has been found to be language promoting (Haebig et al., 2013; Tamis-LeMonda et al., 2001). Follow-in verbal and nonverbal comments, although one adds linguistic information and the other does not, can both serve to sustain and promote child engagement in the interaction.
These findings also highlight structural differences across interaction contexts, where dedicated play time and necessary activities serve different purposes. Follow-in directives were observed more often during necessary activities but may be qualitatively different depending on the context. In book sharing or play, parents might suggest that the child do or say something, whereas they may have a less open-ended and more goal-directed agenda within contexts such as family chores, caregiving, and transitions (Bottema-Beutel et al., 2022; Flynn & Masur, 2007; Holme et al., 2022). These are contexts that, while lower on some constructs that we measured (i.e., time spent in each context and child rate per minute of communication), may be expanded to enhance active engagement, the quality of activities of daily living, and motor development (Iverson, 2022; Roemer et al., 2022).
Limitations and Future Directions
The results of this study must be considered in the context of certain limitations. First, we examined many variables and interaction contexts, for which the number of participants varied. Therefore, given the structure of our data, findings were interpreted with caution, and care was taken to describe patterns without making firm conclusions. Next, the choices families made about what interaction contexts they chose and the time they spent in each activity were not tightly controlled. As a result, we had more power to observe rates of communication during toy play, as families spent the largest proportion of time in this activity. Furthermore, owing to our correlational design, additional child and parent variables that may have varied by choice of, and time spent in, each context may impact and provide other explanations of our findings. Additional work that examines or controls for these variables is warranted. A related limitation is that information about intervention services delivered to children with autism and DD, as well as the training and coaching relative to PVR their parents may have received, was not available. Furthermore, examination of a wider range of culturally relevant interaction contexts across a more diverse sample is needed to reflect children's real-life experiences and identify ways SLPs and EI providers can align their intervention targets with family priorities (Cycyk et al., 2021). Moreover, it is possible that matching children on other developmental characteristics (e.g., expressive vocabulary; Özçalışkan et al., 2016) may have provided additional information about communication and PVR across contexts. Finally, increased participation in everyday activities as a family has been associated with language development and has been found to contribute to school readiness and social–emotional health (Muñiz et al., 2014; Snow & Beals, 2006; Spagnola & Fiese, 2007). It would be interesting to explore these findings further in families with children identified with DD and autism.
Clinical Implications
Caregivers and interventionists may naturally default to toy play as an intervention context, and it is important to target activities in which the child and parent feel successful. However, in this study, we found that parents and children communicated in all contexts, even those, such as family chores, for which interaction was not the primary purpose. Following recommended practices for EI and with the knowledge that communication occurs across everyday activities, SLPs and other providers can coach parents to support children to take a more active role during less practiced activities such as checking the mail or loading safe items into and out of the dishwasher. Providing families with ideas for how to implement intervention strategies throughout the day extends the time in which an interventionist is present. Finally, when conducting communication and language screenings or evaluations in the home, it may be important to examine the rate of communication during activities that do and do not require the child to engage in triadic coordination of attention.
Conclusions
Infants and toddlers learn by engaging with caregivers during the ordinary activities that families do every day. These vary across and within cultures and are highly individualized; however, every family participates in repeated interactions that help them function, form connections with each other, and provide enjoyment for family members (Boyd et al., 2014). This work represents the first known study that has utilized granular observational coding to examine rate per minute of child communication and PVR across interaction contexts in the natural environment in a large sample of toddlers with and without autism and DD. Results provide a glimpse into the dyadic communication that may occur with everyday activities at home, which supports the need for future intervention research and can aid clinicians seeking to identify activities that serve as important contexts for intervention. Targeted intervention strategies that change the developmental trajectories of young children with autism and DD in the home environment, including increasing rate of child communication and enhancing PVR across everyday activities, may be vital to improving their long-term outcomes.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author (A.D.) upon reasonable request.
Acknowledgments
This research was supported in part by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD078410, R01HD065272; PI: Amy M. Wetherby); the National Institute on Deafness and Other Communication Disorders and National Institute of Mental Health (R21DC018128, R01DC007462, R01MH121364, 3R01MH121364-05S1; PI: Amy M. Wetherby); a Cooperative Agreement from the Centers for Disease Control and Prevention (U01DD000304, 1U10DD000064; PI: Amy M. Wetherby); and the U.S. Department of Education, Office of Special Education Programs (H325D120062; PI: Juliann J. Woods). The content is solely the responsibility of the authors and does not necessarily represent the official views of these federal agencies.
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References
Adamson, L. B. (2018). Communication development during infancy. Routledge.
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5).
American Speech-Language-Hearing Association. (n.d.). Early intervention [Practice Portal]. https://www.asha.org/Practice-Portal/Professional-Issues/Early-Intervention/
Bernheimer, L. P., & Weisner, T. S. (2007). “Let me just tell you what I do all day…”: The family story at the center of intervention research and practice Infants & Young Children, 20(3), 192–201.
Binns, A. V., Casenhiser, D. M., Shanker, S. G., & Cardy, J. O. (2022). Autistic preschoolers' engagement and language use in gross motor versus symbolic play settings. Autism & Developmental Language Impairments, 7.
Bornstein, M. H., Haynes, O. M., Painter, K. M., & Genevro, J. L. (2000). Child language with mother and with stranger at home and in the laboratory: A methodological study. Journal of Child Language, 27(2), 407–420.
Bornstein, M. H., Tamis-LeMonda, C., & Haynes, O. M. (1999). First words in the second year: Continuity, stability, and models of concurrent and predictive correspondence in vocabulary and verbal responsiveness across age and context. Infant Behavior & Development, 22(1), 65–85.
Bottema-Beutel, K., Crowley, S., & Kim, S. Y. (2022). Sequence organization of autistic children's play with caregivers: Rethinking follow-in directives. Autism, 26(5), 1267–1281.
Bottema-Beutel, K., & Kim, S. Y. (2021). A systematic literature review of autism research on caregiver talk. Autism Research, 14(3), 432–449.
Boyd, B. A., McCarty, C. H., & Sethi, C. (2014). Families of children with autism: A synthesis of family routines literature. Journal of Occupational Science, 21(3), 322–333.
Brady, N. C., Marquis, J., Fleming, K., & McLean, L. (2004). Prelinguistic predictors of language growth in children with developmental disabilities. Journal of Speech, Language, and Hearing Research, 47(3), 663–677.
Brady, N., Warren, S. F., Fleming, K., Keller, J., & Sterling, A. (2014). Effect of sustained maternal responsivity on later vocabulary development in children with Fragile X syndrome. Journal of Speech, Language, and Hearing Research, 57(1), 212–226.
Brauer, M., & Curtin, J. J. (2018). Linear mixed-effects models and the analysis of nonindependent data: A unified framework to analyze categorical and continuous independent variables that vary within-subjects and/or within-items. Psychological Methods, 23(3), 389–411.
Bruner, J. (1981). The social context of language acquisition. Language and Communication, 1, 155–178.
Cameron-Faulkner, T., Melville, J., & Gattis, M. (2018). Responding to nature: Natural environments improve parent–child communication. Journal of Environmental Psychology, 59, 9–15.
Charman, T., Taylor, E., Drew, A., Cockerill, H., Brown, J. A., & Baird, G. (2005). Outcome at 7 years of children diagnosed with autism at age 2: Predictive validity of assessments conducted at 2 and 3 years of age and pattern of symptom change over time. The Journal of Child Psychology and Psychiatry, 46(5), 500–513.
Cheng, W. M., Smith, T. B., Butler, M., Taylor, T. M., & Clayton, D. (2022). Effects of parent-implemented interventions on outcomes of children with autism: A meta-analysis. Journal of Autism and Developmental Disorders, 53(11), 4147–4163.
Cleave, P. L., & Bird, E. K. R. (2006). Effects of familiarity on mothers' talk about nouns and verbs. Journal of Child Language, 33(3), 661–676.
Cohen, J. (1960). Coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37–46.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Cycyk, L. M., De Anda, S., Moore, H., & Huerta, L. (2021). Cultural and linguistic adaptations of early language interventions: Recommendations for advancing research and practice. American Journal of Speech-Language Pathology, 30(3), 1224–1246.
Delehanty, A., Hooker, J., & Wetherby, A. M. (2023). Verbal responsiveness in parents of toddlers with and without autism during a home observation. Journal of Autism and Developmental Disorders. Advance online publication.
Delehanty, A. D., Stronach, S., Guthrie, W., Slate, E., & Wetherby, A. M. (2018). Verbal and nonverbal outcomes of toddlers with and without autism spectrum disorder, language delay, and global developmental delay. Autism & Developmental Language Impairments, 3.
Delehanty, A. D., & Wetherby, A. M. (2021). Rate of communicative gestures and developmental outcomes in toddlers with and without autism spectrum disorder during a home observation. American Journal of Speech-Language Pathology, 30(2), 649–662.
Division for Early Childhood. (2014). DEC RPs in early intervention/early childhood special education. http://www.dec-sped.org/recommendedpractices
Dowdall, N., Melendez-Torres, G. J., Murray, L., Gardner, F., Hartford, L., & Cooper, P. J. (2020). Shared picture book reading interventions for child language development: A systematic review and meta-analysis. Child Development, 91(2), e383–e399.
Dunst, C. J., & Espe-Sherwindt, M. (2016). Family-centered practices in early childhood intervention. In B. Reichow, B. A Boyd, E. E. Barton, & S. L. Odom (Eds.), Handbook of early childhood special education (pp. 37–55). Springer.
Edmunds, S. R., Kover, S. T., & Stone, W. L. (2019). The relation between parent verbal responsiveness and child communication in young children with or at risk for autism spectrum disorder: A systematic review and meta-analysis. Autism Research, 12(5), 715–731.
Fleury, V. P., & Hugh, M. L. (2018). Exploring engagement in shared reading activities between children with autism spectrum disorder and their caregivers. Journal of Autism and Developmental Disorders, 48(10), 3596–3607.
Fleury, V. P., & Schwartz, I. S. (2017). A modified dialogic reading intervention for preschool children with autism spectrum disorder. Topics in Early Childhood Special Education, 37(1), 16–28.
Flynn, V., & Masur, E. F. (2007). Characteristics of maternal verbal style: Responsiveness and directiveness in two natural contexts. Journal of Child Language, 34(3), 519–543.
Franchini, M., Armstrong, V. L., Schaer, M., & Smith, I. M. (2019). Initiation of joint attention and related visual attention processes in infants with autism spectrum disorder: Literature review. Child Neuropsychology, 25(3), 287–317.
Gros-Louis, J., West, M. J., & King, A. P. (2016). The influence of interactive context on prelinguistic vocalizations and maternal responses. Language Learning and Development, 12(3), 280–294.
Guthrie, W., Swineford, L. B., Nottke, C., & Wetherby, A. M. (2013). Early diagnosis of autism spectrum disorder: Stability and change in clinical diagnosis and symptom presentation. Journal of Child Psychology and Psychiatry, 54(5), 582–590.
Haebig, E., McDuffie, A., & Ellis Weismer, S. (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, 22(1), 57–70.
Harel, D., & McAllister, T. (2019). Multilevel models for communication sciences and disorders. Journal of Speech, Language, and Hearing Research, 62(4), 783–801.
Hatherly, K., Stienwandt, S., Salisbury, M. R., Roos, L. E., & Fisher, P. A. (2022). Routines as a protective factor for emerging mental health and behavioral problems in children with neurodevelopmental delays. Advances in Neurodevelopmental Disorders, 7, 35–45.
Heidlage, J. K., Cunningham, J. E., Kaiser, A. P., Trivette, C. M., Barton, E. E., Frey, J. R., & Roberts, M. Y. (2020). The effects of parent-implemented language interventions on child linguistic outcomes: A meta-analysis. Early Childhood Research Quarterly, 50, 6–23.
Hoff, E. (2010). Context effects on young children's language use: The influence of conversational setting and partner. First Language, 30(3–4), 461–472.
Holme, C., Harding, S., Roulstone, S., Lucas, P. J., & Wren, Y. (2022). Mapping the literature on parent–child language across activity contexts: A scoping review. International Journal of Early Years Education, 30(1), 6–24.
Hyman, S. L., Levy, S. E., Myers, S. M., Kuo, D. Z., Apkon, S., Davidson, L. F., Ellerbeck, K. A., Foster, J. E. A., Noritz, G. H., O'Connor Leppert, M., Saunders, B. S., Stille, C., Yin, L., Weitzman, C. C., Childers, D. O., Jr., Levine, J. M., Peralta-Carcelen, A. M., Poon, J. K., Smith, P. J., … Bridgemohan, C. (2020). Identification, evaluation, and management of children with autism spectrum disorder. Pediatrics, 145(1), Article e20193447.
Individuals with Disabilities Education Improvement Act of 2004, 20 U.S.C. § 1400 et seq. (2004).
Iverson, J. M. (2022). Developing language in a developing body, revisited: The cascading effects of motor development on the acquisition of language. Wiley Interdisciplinary Reviews: Cognitive Science, 13(6), Article e1626.
Kashinath, S., Woods, J., & Goldstein, H. (2006). Enhancing generalized teaching strategy use in daily routines by parents of children with autism. Journal of Speech, Language, and Hearing Research, 49(3), 466–485.
Kover, S. T., Davidson, M. M., Sindberg, H. A., & Weismer, S. E. (2014). Use of the ADOS for assessing spontaneous expressive language in young children with ASD: A comparison of sampling contexts. Journal of Speech, Language, and Hearing Research, 57(6), 2221–2233.
Kuchirko, Y. A., & Tamis-LeMonda, C. S. (2019). The cultural context of infant development: Variability, specificity, and universality. In D. A. Henry, E. Votruba-Drzal, & P. Miller (Eds.), Advances in child development and behavior (Vol. 57, pp. 27–63). Elsevier.
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174.
Lewedag, V. L., Oller, D. K., & Lynch, M. P. (1994). Infants' vocalization patterns across home and laboratory environments. First Language, 14(42–43), 49–65.
Lord, C., Rutter, M., DiLavore, P. C., & Risi, S. (1999). Autism Diagnostic Observation Schedule (ADOS). Western Psychological Services.
McDuffie, A., & Yoder, P. (2010). Types of parent verbal responsiveness that predict language in young children with autism spectrum disorder. Journal of Speech, Language, and Hearing Research, 53(4), 1026–1039.
McHugh, M. L. (2012). Interrater reliability: The kappa statistic. Biochemia Medica, 22(3), 276–282.
McLean, J., & Snyder-McLean, L. (1978). A transactional approach to early language training. Charles E. Merrill.
Miller, J. L., Lossia, A., Suarez-Rivera, C., & Gros-Louis, J. (2017). Toys that squeak: Toy type impacts quality and quantity of parent–child interactions. First Language, 37(6), 630–647.
Mullen, E. M. (1995). Mullen Scales of Early Learning. AGS.
Muñiz, E. I., Silver, E. J., & Stein, R. E. (2014). Family routines and social-emotional school readiness among preschool-age children. Journal of Developmental & Behavioral Pediatrics, 35(2), 93–99.
O'Brien, M., & Bi, X. (1995). Language learning in context: Teacher and toddler speech in three classroom play areas. Topics in Early Childhood Special Education, 15(2), 148–163.
Özçalışkan, Ş., Adamson, L. B., & Dimitrova, N. (2016). Early deictic but not other gestures predict later vocabulary in both typical development and autism. Autism, 20(6), 754–763.
Roemer, E. J., Kushner, E. H., & Iverson, J. M. (2022). Joint engagement, parent labels, and language development: Examining everyday interactions in infant siblings of children with autism. Journal of Autism and Developmental Disorders, 52(5), 1984–2003.
Ross, H. S., & Lollis, S. P. (1987). Communication within infant social games. Developmental Psychology, 23(2), 241–248.
Sameroff, A. (1975). Transactional models in early social relations. Human Development, 18(1–2), 65–79.
Sameroff, A. (2009). The transactional model. In A. Sameroff (Ed.), The transactional model of development: How children and contexts shape each other (pp. 3–21). American Psychological Association.
Schertz, H. H., Baker, C., Hurwitz, S., & Benner, L. (2011). Principles of early intervention reflected in toddler research in autism spectrum disorders. Topics in Early Childhood Special Education, 31(1), 4–21.
Schertz, H. H., & Horn, K. (2018). Facilitating toddlers' social communication from within the parent–child relationship: Application of family-centered early intervention and mediated learning principles. In M. Siller & L. Morgan (Eds.), Handbook of parent-implemented interventions for very young children with autism (pp. 141–154). Springer.
Schreibman, L., Dawson, G., Stahmer, A. C., Landa, R., Rogers, S. J., McGee, G. G., Kasari, C., Ingersoll, B., Kaiser, A. P., Bruinsma, Y., McNerney, E., Wetherby, A., & Halladay, A. (2015). Naturalistic developmental behavioral interventions: Empirically validated treatments for autism spectrum disorder. Journal of Autism and Developmental Disorders, 45(8), 2411–2428.
Slonims, V., & McConachie, H. (2006). Analysis of mother–infant interaction in infants with Down syndrome and typically developing infants. American Journal on Mental Retardation, 111(4), 273–289.
Snow, C. E., & Beals, D. E. (2006). Mealtime talk that supports literacy development. New Directions for Child and Adolescent Development, 2006(111), 51–66.
Soderstrom, M., & Wittebolle, K. (2013). When do caregivers talk? The influences of activity and time of day on caregiver speech and child vocalizations in two childcare environments. PLOS ONE, 8(11), Article e80646.
Spagnola, M., & Fiese, B. H. (2007). Family routines and rituals: A context for development in the lives of young children. Infants & Young Children, 20(4), 284–299.
Sparrow, S., Cicchetti, D. V., & Balla, D. A. (2005). Vineland Adaptive Behavior Scales–Second Edition. AGS.
Tamis-LeMonda, C. S., Bornstein, M. H., & Baumwell, L. (2001). Maternal responsiveness and children's achievement of language milestones. Child Development, 72(3), 748–767.
Tamis-LeMonda, C. S., Custode, S., Kuchirko, Y., Escobar, K., & Lo, T. (2019). Routine language: Speech directed to infants during home activities. Child Development, 90(6), 2135–2152.
Thurm, A., Lord, C., Lee, L. C., & Newschaffer, C. (2007). Predictors of language acquisition in preschool children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 37(9), 1721–1734.
Tulviste, T. (2003). Contextual variability in interactions between mothers and 2-year-olds. First Language, 23(3), 311–325.
Walker, E. A., Redfern, A., & Oleson, J. J. (2019). Linear mixed-model analysis to examine longitudinal trajectories in vocabulary depth and breadth in children who are hard of hearing. Journal of Speech, Language, and Hearing Research, 62(3), 525–542.
Wan, M. W., Green, J., & Scott, J. (2019). A systematic review of parent–infant interaction in infants at risk of autism. Autism, 23(4), 811–820.
Weitzman, E. (2013). More Than Words—The Hanen Program for parents of children with autism spectrum disorder: A teaching model for parent-implemented language intervention. Perspectives on Language Learning and Education, 20(3), 96–111.
Wetherby, A., & Prizant, B. (2002). Communication and Symbolic Behavior Scales: Developmental Profile (1st normed ed.). Brookes.
Wetherby, A. M., Brosnan-Maddox, S., Peace, V., & Newton, L. (2008). Validation of the Infant-Toddler Checklist as a broadband screener for autism spectrum disorders from 9 to 24 months of age. Autism, 12, 487–511.
Wetherby, A. M., & Rodriguez, G. P. (1992). Measurement of communicative intentions in normally developing children during structured and unstructured contexts. Journal of Speech and Hearing Research, 35(1), 130–138.
Wetherby, A. M., Woods, J., Guthrie, W., Delehanty, A., Brown, J. A., Morgan, L., Holland, R. D., Schatschneider, C., & Lord, C. (2018). Changing developmental trajectories of toddlers with autism spectrum disorder: Strategies for bridging research to community practice. Journal of Speech, Language, and Hearing Research, 61(11), 2615–2628.
Wetherby, A. M., Woods, J., Nottke, C., Stronach, S., Dow, D., & McCoy, D. (2016). Systematic observation of red flags of autism spectrum disorder [Unpublished manual]. Florida State University.
Woods, J. J., & Brown, J. A. (2011). Integrating family capacity-building and child outcomes to support social communication development in young children with autism spectrum disorder. Topics in Language Disorders, 31(3), 235–246.
Woods, J. J., Wilcox, M. J., Friedman, M., & Murch, T. (2011). Collaborative consultation in natural environments: Strategies to enhance family-centered supports and services. Language, Speech, and Hearing Services in Schools, 42(3), 379–392.
Yont, K. M., Snow, C. E., & Vernon-Feagans, L. (2003). The role of context in mother–child interactions: An analysis of communicative intents expressed during toy play and book reading with 12-month-olds. Journal of Pragmatics, 35(3), 435–454.
Zwaigenbaum, L., Bauman, M. L., Choueiri, R., Kasari, C., Carter, A., Granpeesheh, D., Mailloux, Z., Roley, S. S., Wagner, S., Fein, D., Pierce, K., Buie, T., Davis, P. A., Newschaffer, C., Robins, D., Wetherby, A., Stone, W. L., Yirmiya, N., Estes, A., … Natowicz, M. R. (2015). Early intervention for children with autism spectrum disorder under 3 years of age: Recommendations for practice and research. Pediatrics, 136(Suppl. 1), S60–S81.
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Published In
American Journal of Speech-Language Pathology
Volume 33 • Number 3 • May 2024
Pages: 1266-1282
PubMed: 38407116
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Copyright © 2024 The Authors. 
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.History
- Received: Aug 28, 2023
- Revised: Nov 24, 2023
- Accepted: Jan 2, 2024
- Published online: Feb 26, 2024
- Published in issue: May 1, 2024
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