Abstract
Purpose:
Children who are deaf or hard of hearing (D/HH) are at increased risk for neurocognitive delays, which can have cascading effects on development. Associations between neurocognition and the content of parental language—specifically the use of mental state vocabulary—have been observed in typically hearing (TH) children. This study investigated the role of parental use of mental state language (e.g., vocabulary related to thought processes, desires, and emotions) in explaining variability in neurocognition in children who are D/HH.
Method:
Dyads of 62 TH and 69 D/HH children who wear hearing aids or cochlear implants (ages 3–8 years) and their primary parent were videorecorded during a 20-min play session. Specific mental state words used by parents were extracted. Child neurocognition (specifically, inhibitory control) was assessed using norm-referenced measures.
Results:
Parent use of mental state language predicted child inhibitory control differentially based on hearing status, with a significant relation in the D/HH but not the TH group. Mental state vocabulary related to cognition (e.g., “think,” “know”), but not to desire (e.g., “want,” “like”) or emotion (e.g., “feel,” “frustrated”), predicted child inhibitory control in the D/HH group. Finally, there was a significant relation between the use of first person, but not second or third person, mental state verbs (e.g., “I think”) and child inhibitory control.
Conclusions:
Parental use of cognitive mental state vocabulary models language around thought processes, and parents' use of first-person referents models “self-talk.” Modeling of these linguistic forms is likely foundational for developing self-regulation. Children who are D/HH often experience reduced auditory access and/or language delays and thus rely on high-quality parental language input for longer periods of development than their TH peers. Continued support from interventionists is indicated to coach parents to be high-quality models of more abstract, decontextualized language, supporting complex language development and inhibitory control in children who are D/HH.
There exists significant variability in neurocognitive outcomes for children who are deaf or hard of hearing (D/HH), which cannot be fully explained by child- or device-related factors alone (e.g., Kronenberger et al., 2013, 2014). Family-level influences (Blank et al., 2020, 2021; Holt et al., 2012), as well as parental linguistic input (Cruz et al., 2013; DesJardin & Eisenberg, 2007; Wang et al., 2017), have been identified as key factors in language and neurocognitive outcomes of children who are D/HH. However, the mechanisms underlying the relation between parental input and child outcomes are not well understood for children who are D/HH. Studies of young children with typical hearing (TH) have demonstrated associations between the content of parental language—specifically, use of vocabulary surrounding mental states—and child performance on tasks assessing neurocognitive abilities. This area of research is of particular importance for children who are D/HH, as they represent a clinical population at risk for neurocognitive delays (Kronenberger et al., 2014). The purpose of this investigation was to evaluate if and how parental use of mental state language is related to neurocognitive development in children who are D/HH. The results could have implications for novel, targeted family-centered intervention that incorporates parent coaching on language used with their child who is D/HH.
Neurocognition in Action: Executive Function and Theory of Mind
Neurocognition is a general term for cognitive processes, particularly as they relate to neural mechanisms or pathways. Executive function is an umbrella term for a group of specific neurocognitive processes—those that, taken together, allow for goal-oriented behavior (Miyake et al., 2000). Executive function includes skills such as working memory, inhibitory control, and sustained attention, among others. The development of executive function begins in the first year of life (Diamond & Goldman-Rakic, 1989) and continues well into adolescence and young adulthood (Center on the Developing Child, 2012) and is crucial for both language (Pisoni et al., 2010) and psychosocial (Castellanos et al., 2018) outcomes. Children who are prelingually D/HH are at increased risk for delays in many areas of executive function, which has the potential for cascading effects on development (e.g., Kronenberger et al., 2014). Identifying sources of variability in executive function skills in children who are D/HH may help guide treatment and intervention.
One factor that contributes to child neurocognitive outcomes (in both typical and clinical populations) is parental linguistic input (Bernier et al., 2010)—specifically, parent use of mental state language (e.g., language that references internal thoughts, feelings, and desires). In examining the effect of parental linguistic influences on child neurocognition, much of the previous research has not focused on executive function tasks to measure neurocognitive abilities but rather children's abilities to complete Theory of Mind tasks. Theory of Mind is defined as the understanding that others possess unique views/thoughts that differ from one's own. Like other areas of development, Theory of Mind development is marked by certain milestones, with the earliest recognition of intentionality and agency believed to begin in infancy (Carlson et al., 2013). The most significant proliferation of skills occurs between the ages of 2 and 5 years, as children begin to understand appearance versus reality discrepancies (Flavell et al., 1983) and show some recognition of varying perspectives on the same scene or event (Flavell et al., 1981). An important milestone in the development of pragmatic competency in children between 2 and 5 years is the understanding of false beliefs or the ability to recognize other people can have thoughts, views, or knowledge that are different from one's own. Example (1) demonstrates a hypothetical scenario presented to a child to assess false-belief understanding:
Example (1). Bert and Ernie are both in the kitchen, and Ernie puts a cookie inside a cookie jar on the counter. When Ernie leaves the room, Bert takes the cookie from the cookie jar and hides it in the cabinet. Ernie comes back into the room, and he wants that cookie. Where will he look for the cookie?
A child with sufficient understanding of false belief would recognize that Ernie will look in the cookie jar, as that is the last place he saw the cookie before leaving the room. When young children without false-belief understanding are asked where Ernie will look for the cookie, they will respond with where the cookie truly is—the cabinet. False belief is only one aspect of Theory of Mind development and measurement; still, it serves as an early and important marker of social-pragmatic abilities.
Although much of the previous research concerning parental influences on child neurocognition has focused on Theory of Mind or false belief as the outcome variable of interest (e.g., Farkas et al., 2018; Roby & Scott, 2018; among others), there is a strong theoretical connection between executive function abilities and false-belief understanding. Executive function abilities—specifically, inhibitory control—are believed to underlie success on false belief or general Theory of Mind tasks (Carlson & Moses, 2001). Inhibitory control is the ability to suppress an automatic or dominant thought or response for an alternative, nondominant response required to successfully perform a task (Brown et al., 2013). This executive function ability is thought to influence children's ability to complete perspective-taking tasks, because these tasks require children to suppress a prepotent response (e.g., the truth about the location of an item in a false-belief task) with the nondominant response of taking on another's point of view, thereby employing inhibitory control abilities (Carlson & Moses, 2001). Brain imaging and behavioral brain studies implicating frontal lobe activitiy for both Theory of Mind (Goel et al., 1995; Sabbagh & Taylor, 2000) and inhibitory control (see, e.g., Luria, 1973) tasks, as well as the similar developmental time course of Theory of Mind and inhibitory control, lend support to the hypothesis that Theory of Mind and inhibitory control might represent two interrelated constructs (Carlson & Moses, 2001). Because inhibitory control is thought to both relate to and promote Theory of Mind development, we chose to examine parental language influences on inhibitory control in children who are D/HH.
Parent Mental State Language and Child Neurocognition
Typically Hearing, Typically Developing Children
Mental state language is vocabulary that references internal working states, such as desires, beliefs, or emotions (e.g., “want,” “think,” or “feel”). Evidence from children with typical hearing suggests that parent use of mental state vocabulary positively affects children's neurocognition. This has been supported in both observational studies (de Rosnay et al., 2004; Laranjo et al., 2014; Meins et al., 2013; Roby & Scott, 2018) and those using self-report questionnaires (Ebert et al., 2017). Meins et al. (2013) and Laranjo et al. (2014) found that parental use of mental state verbs at both 8 and 12 months positively predicted child performance on perspective-taking tasks at 4 years of age. Additionally, child performance on a nontraditional false-belief task (which utilizes anticipatory looks to assess false-belief understanding and thus allows testing children at younger developmental stages than traditional false-belief tasks) at 2.5 years of age is positively correlated with parents' concurrent use of mental state language (Roby & Scott, 2018). Although most studies have focused solely on child neurocognition as the outcome of interest, McMahon and Bernier (2017) argued that child language plays an important mediating role in models connecting parent mental state language and child neurocognition (see the works of Bernier et al., 2017; Laranjo & Bernier, 2013). This finding highlights the important role of parent mental state language in promoting child language competence and the putative relation between language and neurocognition.
Mental state language has been divided into three subcategories: desire, cognition, and emotion. These three subcategories differentially predict children's neurocognitive and spoken language development in children who are TH. For example, parents' use of desire mental state language (e.g., “want”) at 12 months of age was positively correlated with children's receptive and expressive language at 30 months (Farkas et al., 2018), whereas parents' use of cognitive mental state language (e.g., “think,” “know”) predicted children's performance on a perspective-taking task at 30 months (Roby & Scott, 2018). Laranjo et al. (2014) found a positive association between mothers' use of desire and cognition mental state language and child performance on a perspective-taking task, whereas mothers' use of emotion and cognition mental state language predicted child performance on a false-belief task. There is also evidence that the relative frequency of different subcategories of mental state language used by parents changes as children develop, with more cognitive mental state language used with older children (as this category represents the most advanced category of mental state language; Jenkins et al., 2003) and references to desires and emotions decreasing (Farkas et al., 2018) or stabilizing (Taumoepeau & Ruffman, 2008) as children get older. Taken together, there appears to be a strong connection between parent mental state language use and child performance on neurocognitive measures for children with typical hearing.
Clinical Populations
The association between parent mental state language and child neurocognitive outcomes in clinical populations has been studied but to a lesser extent than in children with typical development. Moeller and Schick (2006) analyzed the relation between mother's mental state language use and child performance on a false-belief task in two groups of children: TH (ages 4–6 years) and D/HH children (ages 4–10 years) with normal nonverbal intelligence. Two of the D/HH children were unaided, 10 had cochlear implants (CIs), and 10 used hearing aids (HAs). All of the D/HH children used simultaneous communication (speaking in combination with a manual code of English). The authors reported that mothers' mental state language was related to D/HH children's performance on false-belief tasks; they did not, however, find an association in the control group of TH peers. Notably, the quantity of mothers' overall speech (i.e., transcript length) did not predict D/HH children's performance on false-belief tasks, suggesting that there is something special about the nature of parental mental state language, not just language generally, that allows it to uniquely influence neurocognition in D/HH children. The null findings in the control group of TH children could be due to their age, as typically developing children are able to complete false-belief tasks between ages 4 and 5 years (Wellman et al., 2001), thereby demonstrating little variability in performance.
Further investigating early parent mental state talk in clinical populations, Morgan et al. (2014) examined whether D/HH children from hearing families had appropriate access to this type of early language input. In a cross-cultural study of children using HAs and CIs between ages 17 and 35 months (with an average duration of device use of 7 months) in the United Kingdom and Sweden, the authors found that parents of young D/HH children used significantly less mental state language referencing cognition than parents of hearing children. This difference in mental state word use between parents of TH and D/HH children might be related to the duration of device use in the D/HH sample; parents of D/HH children may be demonstrating sensitivity to their child's more limited auditory experience relative to the TH children. Similar to this finding, parents of TH, language-delayed children (ages 3–5 years) also use significantly fewer mental state words referencing cognition (but not physiological states) compared with parents of age-matched peers with typical language development (Lee & Rescorla, 2008). This discrepancy could be attributed to parental sensitivity to their child's language capabilities.
There is a notable difference in the average ages of the TH, typically developing children versus children with delayed language, and/or hearing loss in much of the previously mentioned literature. Given that children who are D/HH often demonstrate delayed language development (Niparko et al., 2010) and that parent-level influences affect children for longer periods of development than their TH peers (Blank et al., 2020), it logically follows that researchers are interested in studying outcomes in the D/HH population at slightly older ages. A delay in successful completion of false-belief tasks has also been established for children who are D/HH, and therefore examining their performance on these types of tasks at later ages (e.g., after 5 years old, when most TH children successfully complete first-order Theory of Mind tasks) allows for researchers to observe variability and make predictions about sources of this variability.
There is limited research in clinical populations on the association between parent mental state language and specific executive function outcomes—an area of significant risk for D/HH children (Kronenberger et al., 2014). Moeller and Schick (2006) examined D/HH children's performance on false-belief tasks (one element of Theory of Mind), which likely has inhibitory control underpinnings (Carlson & Moses, 2001), but to our knowledge, no studies have directly examined parent mental state language and child inhibitory control effects in children who are D/HH. Prelingually deaf children with CIs are 2–5 times more likely than TH peers to have problems with executive function in the domains of working memory and inhibitory control (e.g., Kronenberger et al., 2014). Deaf children without CIs who are proficient native signers also show elevated risk in the domains of working memory and inhibitory control compared with their hearing peers (Hall et al., 2017). If parent mental state language is related to children's inhibitory control in this clinical population, as it is in TH and typically developing children, this aspect of parent–child interactions could potentially act as a buffer to possible delays in inhibitory control development. Indeed, other aspects of the family environment have been implicated in the development of inhibitory control skills in children who are D/HH including parental stress (Blank et al., 2020) and parental self-reported organizational skills (Holt et al., 2012).
Mechanisms
Several hypotheses have been put forth proposing potential mechanisms explaining the relation between parent mental state language and child neurocognition in typically developing children, all of which involve aspects of language competence. The syntax hypothesis suggests that the use of mental state language models complex syntactic structure and that syntactic competence predicts child Theory of Mind abilities (Astington & Jenkins, 1999; de Rosnay et al., 2004; Milligan et al., 2007; Schick et al., 2007). Increasing semantic competence (i.e., the semantic hypothesis) has also been identified as a potential mediator (de Rosnay et al., 2004), as exposure to decontextualized language fosters child vocabulary growth (Barnes & Dickinson, 2018). Finally, the pragmatic hypothesis proposes that parent modeling of different perspectives allows for an appreciation that others may have perspectives different from one's own (Harris, 2005).
It is difficult to distinguish among these potential mediators (syntactic, semantic, and pragmatic) due to their high degree of correlation with one another (Adrián et al., 2007). For example, one parent utterance modeling mental state verbs will contain a complement clause (syntax), a mental state verb (conveying semantic meaning), and is likely to be a model of a certain perspective (pragmatics). An alternative, but complementary, hypothesis that accounts for these aspects of language competence could be that parent use of “self-talk” provides children with models for working through difficult tasks, ultimately promoting self-regulation. One approach for testing this hypothesis is to analyze subject referents (e.g., first, second, and third person) and their relation to children's understanding of mental states (Harris, 2005). This approach has yielded inconsistent results, with some studies finding children's later understanding of mental state verbs is predicted by references to children's desires (i.e., second-person referents; Taumoepeau & Ruffman, 2006), whereas others found child outcomes to be predicted by references to others' mental states (i.e., third-person referents; Adrián et al., 2007; Barnes & Dickinson, 2018). Studies of child inhibitory control have demonstrated that children's use of self-talk during difficult tasks requiring inhibitory control positively predicts their success on these tasks (Abdul Aziz et al., 2017; Schumacher et al., 2017), suggesting the importance of first-person referents use in children's spoken language. Modeling of self-talk could provide the instruction and practice for how to work through difficult tasks and scaffold the development of self-regulatory abilities.
This Study
The purpose of this study was threefold: (a) to examine parent use of mental state language in conversational exchanges and determine whether parent mental state language predicts child inhibitory control and, if so, whether the relation differs with child hearing status (D/HH vs. TH); (b) to examine the relative contribution of subcategories of parent mental state vocabulary (e.g., cognitive, desire, and emotion) to child inhibitory control; and (c) to preliminarily investigate a potential mechanism through which parent mental state language could be associated with child inhibitory control—parent use of mental state verb subject (e.g., first-person “I” and second-person “you”).
It is predicted that parent use of mental state words will contribute to child inhibitory control in both TH and D/HH children, but that it might be particularly important for D/HH children, given previous findings of an increased sensitivity to parental attributes and linguistic input in this population (Blank et al., 2020; Holt et al., 2012; Moeller & Schick, 2006; Nittrouer et al., 2020). We also predict that the use of cognitive mental state language will drive this relation, given results from Farkas et al. (2018) and Taumoepeau and Ruffman (2008) demonstrating the increasing importance of this mental state word subcategory as children get older. Finally, we will explore mental state verb subject referent—a potential mechanism through which parental mental state language influences child inhibitory control.
Method
Participants
The sample comprised 131 parent–child dyads, including 69 children with mild to profound bilateral sensorineural hearing loss (D/HH group) and 62 children with typical hearing (TH group). All children were between the ages of 3 and 8 years and demonstrated nonverbal cognitive skills within normal limits by earning a T score of at least 30 on the Picture Similarities subscale of the Differential Abilities Scales-II (Elliot, 2007). Of the children who are D/HH, 30 use bilateral HAs and 39 use CIs. All CI users were implanted bilaterally with the exception of two, who both wear an HA in the contralateral ear. Inclusion criteria for children who are D/HH included bilateral mild to profound sensorineural HL; identified with hearing loss and received intervention and hearing technology by 3.5 years (the vast majority was before 2 years of age); if implanted, received the CI by 3.5 years of age; a minimum of 6 months of device use; and a family whose goal was for their child to acquire spoken language. Children who are D/HH were excluded if they had auditory neuropathy spectrum disorder or any neurodevelopmental disorder not directly related to hearing loss (e.g., autism and developmental delay). Children in the TH control group had no known neurodevelopmental disorders and passed a bilateral behavioral hearing screening at 20 dB HL at 0.5, 1, 2, and 4 kHz (re: American National Standards Institute, 2004). All children were enrolled in English-speaking educational programs (intervention or school) and have at least one English-speaking caregiver, with English being the primary language spoken at home. All primary caregivers in both groups had self-reported typical hearing. The sample of primary caregivers (from now on called “parents”) of the D/HH children comprised 62 mothers, four fathers, and three grandmothers (M age = 36.23 years, SD = 6.32); the sample of parents of the TH group included 58 mothers and four fathers (M age = 36.36 years, SD = 5.06).
Table 1 displays demographic and vocabulary data for both groups (including the mean, standard deviation, median, and range for all variables). Additionally, data for the subgroups of D/HH children with HAs and CIs are included in Table 1. All participants (N = 131) with parent mental state language data available were included in these analyses. There are some missing data for other measures due to child inability to complete the measure (Peabody Picture Vocabulary Test [PPVT], n = 1; Flanker task, n = 3) or omission of requested information on demographic questionnaires (n = 1). Those missing data were excluded from the relevant statistical analyses.
Table 1.
Participant demographics.
Variable | TH | D/HH | D/HH subgroup |
|
---|---|---|---|---|
HA | CI | |||
n | 62 | 69 | 30 | 39 |
n male/female/nonbinary | 33/29/0 | 32/37/0 | 13/17/0 | 19/20/0 |
Chronological age, years | ||||
M (SD) | 5.83 (1.57) | 6.28 (1.56) | 6.23 (1.61) | 6.32 (1.53) |
Mdn | 5.7 | 6.44 | 6.17 | 6.77 |
Range | 3.01–8.74 | 3.52–8.97 | 3.76–8.94 | 3.52–8.97 |
Duration of device use, years | ||||
M (SD) | N/A | 4.88 (1.85) | 5.34 (1.87) | 4.52 (1.78) |
Mdn | N/A | 5.20 | 5.47 | 4.51 |
Range | N/A | 0.93–8.69 | 0.93–8.69 | 1.02–7.85 |
Annual family income c | ||||
M (SD) | 7.81 (1.58) | 6.77 (2.60) | 7.45 (2.08) | 6.23 (2.85) |
Mdn | 9* | 8* | 8 | 7 |
Range | 3–9 | 0–9 | 2–9 | 0–9 |
Child receptive vocabulary (PPVT-4 Standard Score) | ||||
M (SD) | 116.32 (10.61) | 94.18 (16.38) | 99.24 (14.69) | 90.41 (16.72) |
Mdn | 116.5*** | 96*** | 98* | 89* |
Range | 96–140 | 55–131 | 64–124 | 55–131 |
Better ear PTA dB HL | ||||
Unaided a | ||||
M (SD) | N/A | 52.45 (16.89) | 47.88 (14.31) | 75.31 (7.32) |
Mdn | N/A | 52.5 | 49.38** | 75** |
Range | N/A | 25–93.75 | 25–93.75 | 67.5–83.75 |
Aided b | ||||
M (SD) | N/A | 24.71 (7.86) | 22.97 (15.48) | 25.23 (3.88) |
Mdn | N/A | 25 | 19.38 | 25 |
Range | N/A | 6.25–36.25 | 6.25–36.25 | 16.25–33.75 |
Note. TH = typical hearing; D/HH = deaf or hard of hearing; HA = hearing aid; CI = cochlear implant; PPVT-4 = Peabody Picture Vocabulary Test–Fourth Edition; PTA = pure-tone average at 500, 1000, 2000, and 4000 Hz; N/A = not applicable.
Data available for subset of participants (D/HH: n = 24, HA: n = 20, CI: n = 4).
Data available for subset of participants (D/HH: n = 35, HA: n = 8, CI: n = 27).
Parents indicated their annual income from the following income brackets: 0 = under $5,000; 1 = $5,000–$9,999; 2 = $10,000–$14,999; 3 = $15,000–$24,999; 4 = $25,000–$34,999; 5 = $35,000–$49,999; 6 = $50,000–$64,999; 7 = $65,000–$79,999; 8 = $80,000–$94,999; and 9 = $95,000 and over.
p < .05.
p < .01.
p < .001.
Tests of group differences across demographic variables were conducted using Mann–Whitney and chi-square tests. There were no significant differences between the subgroups of children with HAs and CIs in chronological age, W = 552.5, p = .70; duration of device use, W = 715, p = .07; child gender, χ2(1) = 0.04, p = .84; and annual family income, W = 727.5, p = .08. However, children with HAs had better receptive vocabulary than children with CIs, W = 747, p = .03. As expected, there was a significant difference between HA and CI users in unaided thresholds, W = 6, p = .006, but not in aided thresholds, W = 109, p = .13 (note that behavioral threshold data are based on a reduced number of children for whom either the parents or the child's audiologist provided their most recent audiogram; see Table 1). HA and CI users were collapsed into one D/HH group to increase statistical power in the analyses. The TH group had a higher average annual family income, W = 1690.5, p = .03, and better child receptive vocabulary, W = 547.5, p < .001, than the D/HH group. Twenty-eight percent (n = 19) of children in the D/HH group scored more than 1 SD below the test mean (100) of the receptive vocabulary test (Peabody Picture Vocabulary Test, Fourth Edition [PPVT-4]). No children in the TH group scored more than 1 SD below the test mean for the PPVT-4. This finding is not surprising given the documented language delays in children who are D/HH (e.g., Niparko et al., 2010). No significant differences were found between TH and D/HH groups on child gender or chronological age, χ2(1) = 0.61, p = .43, and W = 2497.5, p = .10. Because receptive vocabulary and annual family income differed between the groups (and receptive vocabulary differed between the subgroups), these variables were included as covariates in the primary analyses.
Materials
Parent Use of Mental State Language
Parental use of mental state language was analyzed from a 20-min dyadic play interaction with their child that took place in the families' home in a comfortable, well-lit location. There were two primary reasons why we examined parent mental state word use in the context of free-play (in contrast to other settings known to elicit mental state words, such as book reading). First, the home setting provided as natural setting as possible to observe the role of naturalistic parent language in children's outcomes; in fact, parents and children were given the instruction to “play as they normally would.” Second, the decision to focus on a free-play task is supported by a previous work, showing that mental state word used by caregivers in play-based tasks predict later language and social–emotional skills (Farkas et al., 2018) and perspective-taking (Laranjo et al., 2014; Meins et al., 2013).
Parent and child dyads were provided five standard, age-appropriate toys. The same five toys were used for children ages 3–5 years, and a different set of the same five toys were provided to children ages 6–8 years. Families were also provided a blanket and instructed to remain within the boundaries of the blanket during the play interaction, to allow for optimal audio and video recording. Parents and children were instructed to play as they normally would for 15 min, at which point there was a 5-min cleanup period in which children were expected to cleanup independently. Parents were told not to physically help with cleanup, but they could offer verbal support to the child. Parents and children were filmed using a GoPro HERO4 recording system with individual omnidirectional Audio-Technica ATW-1701/L microphones and transmitters.
Parent–child play interaction videos were transcribed and coded for parents' mental state language use in Systematic Analysis of Language Transcripts (Miller & Iglesias, 2012) by two trained research assistants. Transcriptions were checked for congruence by a senior research assistant. In the event of discrepancies between coders, the senior research assistant made the final determination based on video content. The mental state language coding system was adapted from Farkas et al. (2018), using a smaller number of categories to focus on the mental state language subcategories that appear most frequently and consistently in the mental state language literature: desire, emotion, and cognition (see Table 2 for descriptions and examples of each of these three subcategories).
Table 2.
Descriptions and examples of mental state word subcategories used.
Category | Description | Examples |
---|---|---|
Desire | Reference to what one wants, hopes, or wishes for; preferences | Like, love, want, wish |
Emotion | References to emotions or feelings | Feel, happy, sad, upset, disappointed, excited, surprised, jealous, frustrated, worried |
Cognition | References to internal thoughts or cognitive processes | Know, think, believe, understand, guess, remember, forget, imagine, pretend |
A custom Python 3.0 script was run on all transcript files to extract parent utterances containing any of the cognitive, desire, and emotion vocabulary items identified in the literature as encompassing the category of mental state language (Farkas et al., 2018). The lines extracted by the Python program were manually checked, and any utterances with the word “like” being used as a filler or to denote similarity (e.g., “that is just like a puzzle”), or the word “feel” being used as a verb as it relates to touching (e.g., “feel this, it is smooth”) were removed, because they do not represent examples of mental state language within these contexts. The raw total instances of each token (e.g., “think”) were summed, including variations on the word form, such as past tense (e.g., “thought”), present progressive (e.g., “thinking”), or third-person singular (e.g., “thinks”). The raw number of tokens in each of the three subcategories was summed, as well as the grand total of mental state words used by each parent. Converting the total number of mental state word tokens into a proportion over total words or total utterances was considered to control and account for parental verbosity. However, it was determined that the raw number of mental state word tokens better addresses the research questions, in that it is of interest to investigate how frequently children are exposed to these words in a given conversational exchange, not the proportionate use of them by the parent. Ruffman et al. (2002) proposed that measuring the raw amount of mental state talk heard by a child is a more informative measure than using a proportion, providing information on the linguistic input to which they are exposed. de Rosnay et al. (2004) tested raw mental state word counts against proportions and found the exact same impact on their outcome measure of interest. Furthermore, Moeller and Schick (2006) found that mental state talk—not overall maternal linguistic input (i.e., word count)—predicted child Theory of Mind understanding. These studies lend support to operationalizing the parental mental state language variable as token based, as opposed to density based.
Of the total mental state words identified, these were further divided into categories based on the subject referent of the verb: first, second, or third person. Null subjects (e.g., “Remember when we went to Grandma's?”) and infinitive verbs were totaled into an “other” category. Given that the proposed research question aimed to understand the influence of perspective/point-of-view, only first-, second-, and third-person referents were analyzed; those in the other “other” category were omitted from further analysis for this research question only.
Child Receptive Vocabulary
Receptive vocabulary was assessed using the PPVT-4 (Dunn & Dunn, 2007). During the assessment, the child selected each auditorily presented word from a closed set of four pictures. The PPVT-4 has been normed for ages 2 years, 6 months to 90 years+, and standard scores were used in all analyses.
Child Inhibitory Control
The Flanker Inhibitory Control and Attention Test (Flanker) of the NIH Toolbox iPad Cognition Battery Application (Gershon et al., 2013) was administered to children to assess their ability to attend to important information to complete a goal-oriented task, while disregarding distracting information. Children were presented with arrows and fish (ages 3–7 years) or only arrows (ages 8+ years) and asked to indicate the direction of the target (middle) arrow/fish in the presence of arrows/fish that point in either the same (facilitative) or the opposite direction (distracting) as the target arrow/fish. Scores are calculated based on both accuracy and reaction time and are compared with test norms for each child's age.
Procedure
Data were collected during an in-home visit by two clinical researchers with extensive training in speech-language pathology, audiology, and/or pediatric hearing loss. Child language and inhibitory control data were evaluated prior to the video-recorded parent–child play interaction. Parents and children were compensated with gift cards, and the child selected a book from age-appropriate options. The research was approved by the local institutional review board, and parent consent and child assent (when appropriate) were obtained prior to study participation.
Data Analysis
Statistical analyses were performed using R Version 4.1.1 (R Core Team, 2021). Shapiro–Wilks Normality Test was run on all variables of interest, and nearly all variables had nonnormal distributions. Therefore, group differences for demographic, direct-measure, and observation-based variables were evaluated using Mann–Whitney and chi-square tests. Multiple linear regression analyses were performed to identify shared variability among parent mental state word use, child vocabulary and child inhibitory control, and parent/child demographic characteristics. Interaction terms were entered into regression analyses to assess potential interactions between parent language variables and child hearing status on inhibitory control. The criterion for significance for these measures was set at p < .05.
Results
Table 3 displays medians, range, means, and standard deviations for child inhibitory control and parental mental state language use for each participant group (TH and D/HH) and for the D/HH subgroups (HA and CI). Mann–Whitney tests were run to compare group medians of child inhibitory control and parents' use of mental state words between the TH and D/HH groups. As expected, children in the TH group had higher Flanker scores (i.e., better inhibitory control) than the children who are D/HH, W = 1261, p < .001. Eight percent (n = 5) of children in the TH group scored more than 1 SD below the test mean of the Flanker task. In the D/HH group, 26% (n = 18) of children scored more than 1 SD below the mean (10 CI users, and eight HA users). The 26% of children in the D/HH group scoring 1 or more SDs below the test mean is greater than the expected 16% below the mean observed in a normal distribution and is consistent with the literature reporting a greater than expected percentage of children who are D/HH with executive function weaknesses (e.g., Kronenberger et al., 2014). Parents of TH children used more mental state words overall, W = 1615.5, p = .016, more cognitive mental state words, W = 1470, p = .002, and more first-person subject referents, W = 1497, p = .003, than parents of children who are D/HH. No significant group differences were observed for number of desire and emotion mental state words or second- and third-person subject referents. Given that frequency of emotion mental state words and third-person referents were so low for both groups—accounting for less than 2% and 4% of mental state words, respectively—these subcategories of mental state words were not included in the remaining analyses. Although the HA and CI subgroups were collapsed for increased power in subsequent regression analyses, child inhibitory control scores and parent mental state language use for each of these subgroups are reported in Table 3. There were no significant differences between the HA and CI subgroups on any of these variables, further justifying the decision to collapse these subgroups into one D/HH group.
Table 3.
Descriptive statistics for child inhibitory control and parental mental state words.
Variable | TH group | D/HH group | D/HH subgroup |
|
---|---|---|---|---|
HA | CI | |||
Child inhibitory control (Flanker Standard Score) | ||||
M (SD) | 100.7 (13.60) | 90.44 (16.64) | 90.93 (18.90) | 90.05 (14.88) |
Mdn | 100*** | 90*** | 89 | 90 |
Range | 63–147 | 38–124 | 38–123 | 38–124 |
Parent total MSWs (n) | ||||
M (SD) | 37.76 (13.04) | 32.49 (16.69) | 34.37 (20.34) | 31.05 (12.33) |
Mdn | 35* | 31* | 32.5 | 31 |
Range | 17–76 | 6–93 | 6–93 | 8–58 |
Cognitive MSW | ||||
M (SD) | 25.26 (9.90) | 20.20 (12.43) | 21.07 (14.89) | 19.53 (10.3) |
Mdn | 24.5** | 19** | 17.5 | 20 |
Range | 9–57 | 0–70 | 3–70 | 0–47 |
Desire MSW | ||||
M (SD) | 12.24 (6.35) | 11.68 (7.96) | 12.7 (9.01) | 10.90 (7.07) |
Mdn | 10.5 | 9 | 13 | 11 |
Range | 2–34 | 0–41 | 1–41 | 0–30 |
Emotion MSW | ||||
M (SD) | 0.31 (0.74) | 0.59 (1.03) | 0.6 (1.12) | 0.6 (0.93) |
Mdn | 0 | 0 | 0 | 0 |
Range | 0–3 | 0–4 | 0–3 | 0–4 |
First-person subject referent | ||||
M (SD) | 18.19 (7.13) | 14.68 (9.11) | 14.97 (10.92) | 14.46 (7.56) |
Mdn | 18** | 13** | 12.5 | 13 |
Range | 5–35 | 0–48 | 2–48 | 0–33 |
Second-person subject referent | ||||
M (SD) | 16.32 (8.07) | 15.26 (10.54) | 17.37 (12.82) | 13.64 (8.20) |
Mdn | 14.5 | 12 | 13 | 11 |
Range | 5–45 | 1–53 | 1–53 | 1–41 |
Third-person subject referent | ||||
M (SD) | 1.16 (1.73) | 1.22 (1.67) | 1.17 (1.76) | 1.26 (1.62) |
Mdn | 1 | 0 | 0 | 1 |
Range | 0–9 | 0–7 | 0–5 | 0–7 |
Note. TH = typical hearing; D/HH = deaf or hard of hearing; HA = hearing aid; CI = cochlear implant; MSW = mental state word.
p < .05.
p < .01.
p < .001.
Pearson correlations were run to assess the relation between parent mental state word use and child receptive vocabulary. Significant positive correlations were found between child language level (as measured by standard scores on the PPVT-4) and the total number of mental state words (r = .52, p < .001) and total number of cognitive mental state words (r = .42, p < .001) used by parents of children who are D/HH. No significant correlations were found in the TH group. Furthermore, correlations between child chronological age and parent use of mental state words were not significant.
Regression analyses. Multiple linear regression analyses were used to identify how much variability in child inhibitory control could be accounted for by parent mental state word use and child hearing status while controlling for child receptive vocabulary and annual family income. Unsurprisingly, a high degree of collinearity was found between hearing group and child receptive vocabulary, r(128) = .625, p < .001. Therefore, receptive vocabulary was omitted from the models that include hearing group to reduce the chance of confounded findings resulting from this collinearity.
The first regression model predicted child inhibitory control from parents' total mental state language use (total number of mental state words), child hearing status, and the interaction between child hearing status and parent total mental state language, controlling for annual family income. The resulting model was significant, F(4, 123) = 5.91, p < .001, R 2 = .16, with hearing group, parent total mental state word use, and their interaction significantly predicting child inhibitory control (see Table 4). Annual family income was not a significant predictor. The interaction between hearing group and parent use of mental state words is displayed in Figure 1. Parents of children who are D/HH who used a higher total number of mental state words during dyadic play had children with better inhibitory control; no relationship was observed for TH children.
Table 4.
Linear regression model results predicting child inhibitory control from hearing group, parent use of mental state words (MSWs), and their interaction.
Variable | b | t score | p value |
---|---|---|---|
Intercept (hearing group: D/HH) | 84.09 | 16.73 | < .001*** |
Hearing group: TH | 23.68 | 3.20 | .002** |
Total MSWs | 0.34 | 2.92 | .004** |
Hearing Group × Total MSWs interaction | −0.39 | −2.02 | .045* |
Annual family income | −0.68 | −1.06 | .29 |
Note. Given the categorical nature of the hearing group variable, the deaf or hard of hearing (D/HH) group represents the intercept (i.e., the predicted value of the outcome variable when hearing group is set to 0). The hearing group: Typical hearing (TH) variable represents the estimated difference in the predicted value of the outcome variable between the typically hearing and D/HH groups.
p < .05.
p < .01.
p < .001.
Figure 1.
Scatter plot and regression lines showing the association (or lack thereof) between child inhibitory control and total parent mental state words as a function of hearing status. TH = typically hearing; D/HH = deaf or hard of hearing; MSWs = mental state words.
A second model was run to explore the contributions of subcategories of mental state words to child inhibitory control in the D/HH group only. The decision to focus the remaining analysis on the D/HH group was based on results from the first regression model, which showed a lack of correlation between parent use of mental state words and child inhibitory control in the TH group. Only the cognitive and desire subcategories of mental state words were included in this model, because emotion mental state words were used so infrequently and could lead to spurious results if included. Thus, the model predicted child inhibitory control from total number of cognitive and desire mental state words; annual family income and child receptive vocabulary were entered as covariates. The resulting model was significant, F(4, 62) = 3.98, p = .006, R 2 = .204 (see Table 5). The number of cognitive mental state words, but not desire mental state words, used by parents accounted for a significant amount of variability in child inhibitory control. It is worth noting that this relationship was significant even with child vocabulary contributing significantly to the variability in inhibitory control. Figure 2 displays the relation between D/HH children's inhibitory control and parental use of cognitive and desire mental state words.
Table 5.
Contribution of mental state word (MSW) subcategories in predicting child inhibitory control in deaf or hard of hearing (D/HH) children.
Variable | b | t score | p value |
---|---|---|---|
Intercept | 60.86 | 5.34 | < .001*** |
Cognitive MSWs (count) | 0.43 | 2.52 | .014* |
Desire MSWs (count) | −0.27 | −1.05 | .30 |
Child receptive vocabulary (PPVT-4 standard score) | 0.35 | 2.22 | .03* |
Annual family income | −1.29 | −1.40 | .17 |
Note. MSW = mental state word; PPVT-4 = Peabody Picture Vocabulary Test–Fourth Edition.
p < .05.
p < .001.
Figure 2.
Scatter plot and regression lines for child inhibitory control and parent use of cognitive and desire mental state words in children who are deaf or hard of hearing (D/HH). MSWs = mental state words.
Finally, a third model was run to address the question of the role of subject referents in predicting child inhibitory control in the D/HH group only, given that a relation between mental state word variables and child inhibitory control was found only in this group from the first regression model. This third model predicted child inhibitory control from the number of first and second person, subject referents for mental state verbs only (not all verbs used by parents), with annual family income and child receptive vocabulary entered as covariates. As with the emotion variable in the second model, third-person referents were omitted from this third model, given their infrequent use by parents. The resulting model was significant, F(4, 62) = 3.41, p = .014, R 2 = .118 (see Table 6). The number of first-person subject referents for mental state verbs was the only significant predictor of child inhibitory control in this model, p = .029. This relationship was significant even with child vocabulary reaching significance in the model. Parent use of second-person subject referents was not significant.
Table 6.
Contribution of mental state verb subject referent in predicting child inhibitory control in children who are deaf or hard of hearing (D/HH).
Variable | b | t score | p value |
---|---|---|---|
Intercept | 60.03 | 5.17 | < .001*** |
First-person referents (count) | 0.51 | 2.24 | .029* |
Second-person referents (count) | −0.01 | −0.53 | .96 |
Child receptive vocabulary (PPVT-4 standard score) | 0.33 | 2.04 | .046* |
Annual family income | −1.10 | −1.17 | .25 |
Note. PPVT-4 = Peabody Picture Vocabulary Test–Fourth Edition.
p < .05.
p < .001.
Discussion
The threefold purpose of the study was to investigate differences in the impact of parent mental state language on inhibitory control in children with and without hearing loss; determine if certain subcategories of mental state language contributed more to inhibitory control than others; and explore a potential mechanism through which parent mental state word use is associated with child inhibitory control.
Parents of children with TH used significantly more mental state words overall and significantly more cognitive mental state words than parents of children who are D/HH, consistent with Morgan et al. (2014), who similarly found parents of children who are D/HH using significantly fewer cognitive mental state verbs than their control group of hearing peers. Given that children who are D/HH often show a protracted period of language delay (e.g., Niparko et al., 2010), perhaps parents of children who are D/HH use fewer mental state words (and specifically, cognitive mental state words) due to their sensitivity to their child's language—and not chronological age—level. Significant results from correlational analyses between child language and total number of mental state words and total number of cognitive mental state words in the D/HH group (but not the TH) support this conclusion. Furthermore, no significant correlations were found for child chronological age with total mental state word use or cognitive mental state word use by parents in the D/HH group. These results suggest that parents in this study may have used fewer mental state words in response to their child's language level. In other words, they are sensitive to their child's language skills and are adjusting how they talk to their children accordingly—in this case, using more mental state words, including cognitive ones, with children who have better receptive vocabulary. This tendency for parents to adjust their language to their child's language level is well established in TH and typically developing children. For example, Roy (2009) found that parents “fine-tune” their linguistic input, decreasing and then increasing their utterance length and complexity when introducing an unfamiliar word. However, expectations for parent linguistic input in children who are D/HH is a bit more complicated, as variation in language levels and “hearing age” (i.e., duration of device use) makes finding the desirable zone of proximal development (Vygotsky, 1978) more difficult. Fagan et al. (2014) investigated parental contingent responses to child vocalizations before and after cochlear implantation and found a decrease in parental linguistic complexity postimplant as compared with age-matched peers. These results suggest an increased sensitivity by parents of children with CIs to their child's language level, rather than their chronological age, by responding appropriately based on their child's linguistic abilities. Results from this study are consistent with Fagan et al. (2014) and extend them to mental state language, supporting the notion that parents of children who are D/HH demonstrate sensitivity to their child's language levels by adjusting certain characteristics of their own language use with their child.
Farkas et al. (2018) demonstrated that the nature of parental mental state word use changes as children grow and develop from infancy to young children. Early mental state word input is comprised mostly of desire vocabulary, given its increased salience through contextually relevant visual cues (such as facial expressions), shifting to use of more cognitive and fewer desire and emotion mental state word once the child is able to acquire a more nuanced understanding of cognitive states, devoid of concrete context cues (Taumoepeau & Ruffman, 2008). Children in the D/HH group were slightly (although not significantly) older than in the TH group. However, when comparing the chronological age of the TH group with the duration of device use (i.e., duration of auditory access) of the two D/HH subgroups, children with CIs and HAs had about 1 and 0.5 fewer years (respectively) of auditory access than their hearing peers. Furthermore, there was a 1- and 2-year discrepancy between the chronological age and duration of device use for the HA and CI users, respectively. The fact that parents of children who are D/HH are using fewer cognitive mental state words than parents of similarly aged hearing peers suggests that parents of D/HH children are sensitive to this auditory access delay. These parents are providing language models appropriate for their “hearing age” (i.e., amount of time since auditory access began) rather than their chronological age.
TH Results
We did not find a significant association between parents' use of mental state words and child inhibitory control in the TH group. Although not run as part of the formal analysis, specific subcategories of mental state words also did not predict inhibitory control in the TH group: cognitive, p = .88; desire, p = .84. Previous research has demonstrated a significant relation between overall mental state words use, as well as specific subtypes, with child neurocognitive outcomes in TH populations (Bellagamba et al., 2014; Taumoepeau & Ruffman, 2008). A potential reason for the discrepancy in results between previous work and this study could be the relative ages of participants. While the average age of child participants in this study was around 6 years, previous studies have focused on children at earlier ages in development (e.g., 18–24 months in Bellagamba et al., 2014; and 15–33 months in Taumoepeau & Ruffman, 2008). It is possible that the window of effect for this type of parental linguistic influence on child inhibitory control occurs either at younger chronological or language ages than the TH children included in this study. When children are very young, such as the ages in Bellagamba et al. (2014) and Taumoepeau and Ruffman (2008), their language input likely comes primarily from the home environment. By the time that children reach school age, not only do sources of language input diversify (e.g., language input from teachers and peers) but also their language competence increases greatly, perhaps making them less reliant on or influenced by these specific aspects of parental linguistic input. The decreasing reliance on parent linguistic input at these older ages could explain the lack of association found between parent mental state word use and child inhibitory control in the TH children in this study.
D/HH Results
Unlike the TH group, there was a positive relation between parent total mental state word use and inhibitory control in children who are D/HH. Furthermore, parents who used more cognitive mental state words tended to have D/HH children with better inhibitory control. This same relation was not observed for use of desire mental state words. Results from this study support and extend the results of Moeller and Schick (2006), who found that parents of TH children used significantly more mental state language than parents of children who are D/HH; however, their data revealed a positive association between parent use of mental state language and child performance on false-belief task in D/HH children and not in TH children—much like the results of this study. The average age of both TH (M = 5.0 years) and D/HH children (M = 6.9 years) in their study aligns closely with the average age of children in this study. Unlike the developmental trajectory of their TH peers, children who are D/HH often do not reach the same level of language competence by the time they reach early school ages (e.g., Niparko et al., 2010) and are known to benefit less from incidental learning than their TH, age-matched peers (Convertino et al., 2014). Therefore, both these data and the results of Moeller and Schick (2006) suggest that parental linguistic input may continue to play a significant role in influencing developmental outcomes at later chronological ages for children who are D/HH.
Comparing D/HH and TH Results
Findings from this study suggest that inhibitory control in children with hearing loss may be more sensitive to and dependent on certain aspects of parental linguistic input than their TH peers, and/or possibly that this period of sensitivity to parent input lasts for longer than their TH peers. This finding is supported by a growing body of literature that suggests that parent and family influences on developmental outcomes may persist into later chronological ages for D/HH children as compared with their TH peers (Blank et al., 2020, 2021; Nittrouer et al., 2020). In a study comparing the effect of parental stress on inhibitory control and language outcomes in children, Blank et al. (2020) found that language and inhibitory control outcomes only in children who are D/HH were related to parent stress; no relation was found for TH children. Nittrouer et al. (2020) examined the effect of the quantity and quality of parental linguistic in the preschool years on children's language in the short- and long-term for TH and D/HH children, concluding that the language in children with TH demonstrated limited influence from their parent's language input, whereas language in children with HAs and CIs was affected by both the quantity and quality of parent language input. In each of these studies, parent-level variables (i.e., stress and language) were measured when children were, on average, between 4 and 6 years old. Given that numerous studies examining influence of parent mental state language on child neurocognitive outcomes in the TH population have found significant results when studying children under 36 months (e.g., Bellagamba et al., 2014; Taumoepeau & Ruffman, 2008), it is likely that the older age of children in this study contributed to the null findings in the TH group. This study provides additional support to the notion that there may be a protracted period of sensitivity to parent-level influences on development for children who are D/HH.
Mechanism Exploration
Given the association found between parent use of mental state words and child inhibitory control in the D/HH group, we explored a possible mechanism that might account for this association. It has been suggested that modeling of some aspect of language competence—syntactic, semantic, or pragmatic—accounts for this relationship, but disambiguating one from another can be difficult in research relying on observations of parent language (Adrián et al., 2007). This study proposes a hypothesis that modeling of “self-talk”—as opposed to modeling of a particular aspect of language competence—accounts for the association between parent mental state word use and child inhibitory control. Self-talk involves talking through (either vocally or subvocally) a problem or situation from the first-person perspective. We examined the role of subject referents as preliminary evidence for this “self-talk” hypothesis and elucidate the nature of the relation between parent mental state word use and child neurocognitive outcomes.
Supporting our hypothesis, we found that first-person referents, but not second- or third-person referents, significantly predicted inhibitory control in children who are D/HH. Harris (2005) proposed that parents' modeling of mental state language provides opportunities for their children to view and appreciate different perspectives. Taumoepeau and Ruffman (2006) found that mothers' references to children's (i.e., second-person referents) desires at 15 months during a book-reading task predicted later child understanding of mental state verbs at 24 months. Conversely, it has also been suggested that mothers' (Adrián et al., 2007) and teachers' (Barnes & Dickinson, 2018) references to others' (i.e., third-person referents) mental states during a book reading task were related to children's later understanding of mental states and receptive vocabulary, respectively. Adrián et al. (2007) concluded that the differences in children's ages between their study and that of Taumoepeau and Ruffman (2006) accounts for the discrepancies in these results; children in the study of Adrián et al. (2007) were between 3 and 7 years of age over the course of the longitudinal study, with a mean age of 4.7 years at Time 1 and 5.9 years at Time 2. The differences in results between this study and previous investigations are likely related to the task. In Taumoepeau and Ruffman (2006) and Adrián et al. (2007), subject referents on mental state words of parents were measured during a book reading task, which lends itself to the discussion of internal working states of others (e.g., characters in the book). In this study, parents and children played with toys, some of which required cognitive flexibility (e.g., Legos, puzzle ball), and therefore provided parents the opportunity to model some of the language needed to work through these more difficult tasks. On the other hand, the differences in outcome variables could also account for the discrepancy in results. Although all studies investigated outcomes related to neurocognition, the variable of interest in Taumoepeau and Ruffman (2006) and Adrián et al. (2007) was children's understanding of mental state words, whereas the variable of interest in this study was a behavioral measure of child inhibitory control. Results from this study suggest that parent modeling of self-talk through use of first-person referents is related to children's self-regulatory abilities, as opposed to simply their exposure to mental state vocabulary.
This study focused on parents' use of mental state words and subject referents corresponding to those verbs. Other researchers have also studied children's use of mental state words (Bellagamba et al., 2014; Brown et al., 1996) and self-talk (Abdul Aziz et al., 2017; Schumacher et al., 2017) and their association with neurocognition. Bellagamba et al. (2014) reported that the internal state vocabulary used by 18- to 24-month-old children (measured through parent questionnaire of child expressive mind-related vocabulary) was positively related to children's inhibitory control skills, measured using a reverse categorization task. Brown et al. (1996) found that children's use of mental state vocabulary was associated with performance on false-belief tasks. Investigating the effect of sleep on response inhibition and self-regulation in typically developing children, Schumacher et al. (2017) found improved performance when children independently utilized self-talk. Abdul Aziz et al. (2017) measured standardized testing performance and inhibitory control in children with specific language impairment and similarly found improved performance in the group using self-talk. Taken together, these studies suggest that children's use of mental state words and self-talk is associated with stronger neurocognitive abilities. Given the benefits associated with use of self-talk in difficult tasks, it follows that parents' modeling of self-talk could positively affect children's self-regulatory abilities. The hypothesis suggesting that modeling of “self-talk” acts as the mechanism through which parent use of mental state words influences child inhibitory control combines aspects of the syntactic, semantic, and pragmatic hypotheses, in that “self-talk” includes cues from all of these components of language competence. Modeling self-talk might scaffold its use by children to help support self-regulatory skills. A longitudinal study examining the role of child self-talk in the association between parent self-talk (i.e., first-person subject referents on mental state verbs) and child neurocognitive outcomes would be important in examining the hypothesis that parent mental state word use provides the “self-talk” models necessary for children to work through difficult tasks requiring self-regulation.
Clinical Implications
Results from this study highlight the importance of the quality of language input for children who are D/HH, extending previous results to mental state language. Modeling language around internal working states allows children to “peek into” the mind of another person and models the language required for successful perspective taking (Peters et al., 2009) while also exposing children to the language required to work through more difficult or complex executive function tasks (Abdul Aziz et al., 2017; Schumacher et al., 2017). Much of the focus of intervention targeted toward D/HH children involves expanding their speech and language abilities. For example, parents of young D/HH children are instructed to use facilitative language techniques—such as labeling, expansions, and imitation—to support their child's language development within the context of daily parent–child interactions (Cruz et al., 2013). These early intervention strategies make language learning and development concrete, and rightfully so, as the primary goal is for children to develop language. However, becoming a facile and competent spoken language user requires mastery of the more abstract or decontextualized aspects of language. Exposure to abstract or decontextualized language could facilitate the development of executive function skills, which in turn serve to support later academic skills (Berninger et al., 2017) and psychosocial outcomes (Castellanos et al., 2018). This study proposes that parent modeling of self-talk provides the scaffolding for children to develop the internal dialogue necessary for the development of self-regulatory skills. Parents' roles as language modelers/teachers should continue to be emphasized even as children progress out of the early intervention stages and into more advanced language acquisition and usage.
Limitations and Future Directions
This study has some limitations that could be addressed in future research. First, only one measure of inhibitory control was used in the analysis. Combining indirect and direct measurements of inhibitory control as well as other aspects of executive function skills in children and adults has been suggested as a way to more fully describe and obtain an ecologically valid picture of executive function (Anderson, 2002). However, recent research attempting to correlate behavior-based executive function measurements with questionnaire-based assessments suggests that these two approaches might be measuring different underlying constructs (Magimairaj, 2018; McAuley et al., 2010; O'Meagher et al., 2019; Toplak et al., 2013). A confirmatory factor analysis using the behavior-based and questionnaire-based measurements would be required to create an “inhibitory control” construct to serve as an outcome variable. As this was outside the scope of this study, a single measure of inhibitory control was selected. Another limitation of the current work is that the present analyses are indicative of a relation between parents' use of cognitive mental state verbs and child inhibitory control, but the results cannot speak to the causality or directionality in the relationship. A longitudinal study investigating the effect of parent mental state word use at Time Point A and child executive function at Time Point B (and the reverse), using a cross-lagged regression analysis, could better establish causal relationships. A third limitation relates to both the context of data collection as well as toy selection, and how these choices may have influenced categories of mental state words used by parents. Farkas et al. (2018) found significant differences in type of mental state talk depending on context, with more physiological state references (e.g., tired, hungry) during free-play and more cognitive and emotion talk in a story-telling context. This study aimed to examine parent mental state word use in a naturalistic play setting with minimal tester influence by collecting data in families' homes without the tester physically present in the play space. However, future work could consider examining use of these different categories across multiple settings to allow for observation of more diverse mental state words. Similarly, toy selection may have impacted mental state words elicited. Toys were consistent within 3- to 5-year-olds and within 6- to 8-year-olds; however, some chose to play with only one or two toys, whereas others played with all toys. Anecdotally in our study, toys that had animacy (e.g., farm Lego set with people and animals) tended to elicit more emotion mental state language than those that did not (e.g., puzzle ball). Thus, toy selection could have impacted the results from this study and could be considered in future work to elicit certain types of mental state words.
Conclusions
Results from this study suggest that parental modeling of “self-talk” is related to child self-regulatory abilities and highlight the importance of high-quality parental language input in children who are D/HH beyond the early language learning years. Furthermore, these findings emphasize the need for continued support from speech-language pathologists and interventionists as children move into elementary school, by providing parent education and coaching in the use of higher level and more abstract language with their children. The extant literature on child language development in children who are D/HH beyond the early language years is quite limited; this study serves to add to this nascent but important body of work. The findings from this study could be used to inform clinical practice in working with families of children with hearing loss, highlighting the importance of parent training on modeling of self-talk, and for interventionist support as children progress in their abstract language abilities to buffer against the possible neurocognitive delays frequently observed in this clinical population.
Data Availability Statement
The data sets generated and/or analyzed during this study are available from the corresponding author on reasonable request.
Acknowledgments
This research was funded by National Institute on Deafness and Other Communication Disorders Grant R01014956. The authors would like to acknowledge the significant contributions to video/transcript coding by Amanda Heath, Colleen O'Malley, Kim Siegel, and Shrishti Shrivastava and to data collection and thoughtful feedback by Izabela Jamsek, Kristina Bowdrie, Shirley C. Henning, and Caitlin J. Montgomery.
Funding Statement
This research was funded by National Institute on Deafness and Other Communication Disorders Grant R01014956.
References
- Abdul Aziz, S. , Fletcher, J. , & Bayliss, D. M. (2017). Self-regulatory speech during planning and problem-solving in children with SLI and their typically developing peers. International Journal of Language & Communication Disorders, 52(3), 311–322. https://doi.org/10.1111/1460-6984.12273 [DOI] [PubMed] [Google Scholar]
- Adrián, J. E. , Clemente, R. A. , & Villanueva, L. (2007). Mothers' use of cognitive state verbs in picture-book reading and the development of children's understanding of mind: A longitudinal study. Child Development, 78(4), 1052–1067. https://doi.org/10.1111/j.1467-8624.2007.01052.x [DOI] [PubMed] [Google Scholar]
- American National Standards Institute. (2004). Methods for manual pure-tone threshold audiometry (ANSI S3.21–2004 R2009).
- Anderson, P. (2002). Assessment and development of executive function (EF) during childhood. Child Neuropsychology, 8(2), 71–82. https://doi.org/10.1076/chin.8.2.71.8724 [DOI] [PubMed] [Google Scholar]
- Astington, J. W. , & Jenkins, J. M. (1999). A longitudinal study of the relation between language and theory-of-mind development. Developmental Psychology, 35(5), 1311–1320. https://doi.org/10.1037//0012-1649.35.5.1311 [DOI] [PubMed] [Google Scholar]
- Barnes, E. M. , & Dickinson, D. K. (2018). Relationships among teachers' use of mental state verbs and children's vocabulary growth. Early Education and Development, 29(3), 307–323. https://doi.org/10.1080/10409289.2018.1440844 [Google Scholar]
- Bellagamba, F. , Laghi, F. , Lonigro, A. , Pace, C. S. , & Longobardi, E. (2014). Concurrent relations between inhibitory control, vocabulary and internal state language in 18- and 24-month-old Italian-speaking infants. European Journal of Developmental Psychology, 11(4), 420–432. https://doi.org/10.1080/17405629.2013.848164 [Google Scholar]
- Bernier, A. , Carlson, S. M. , & Whipple, N. (2010). From external regulation to self-regulation: Early parenting precursors of young children's executive functioning. Child Development, 81(1), 326–339. https://doi.org/10.1111/j.1467-8624.2009.01397.x [DOI] [PubMed] [Google Scholar]
- Bernier, A. , McMahon, C. A. , & Perrier, R. (2017). Maternal mind-mindedness and children's school readiness: A longitudinal study of developmental processes. Developmental Psychology, 53(2), 210–221. https://doi.org/10.1037/dev0000225 [DOI] [PubMed] [Google Scholar]
- Berninger, V. , Abbott, R. , Cook, C. R. , & Nagy, W. (2017). Relationships of attention and executive functions to oral language, reading, and writing skills and systems in middle childhood and early adolescence. Journal of Learning Disabilities, 50(4), 434–449. https://doi.org/10.1177/0022219415617167 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Blank, A. , Frush Holt, R. , Pisoni, D. B. , & Kronenberger, W. G. (2020). Associations between parenting stress, language comprehension, and inhibitory control in children with hearing loss. Journal of Speech, Language, and Hearing Research, 63(1), 321–333. https://doi.org/10.1044/2019_JSLHR-19-00230 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Blank, A. , Holt, R. F. , Pisoni, D. B. , & Kronenberger, W. G. (2021). Family-level executive functioning and at-risk pediatric hearing loss outcomes. Journal of Speech, Language, and Hearing Research, 64(1), 218–229. https://doi.org/10.1044/2020_JSLHR-20-00342 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Brown, E. D. , Ackerman, B. P. , & Moore, C. A. (2013). Family adversity and inhibitory control for economically disadvantaged children: Preschool relations and associations with school readiness. Journal of Family Psychology, 27(3), 443–452. https://doi.org/10.1037/a0032886 [DOI] [PubMed] [Google Scholar]
- Brown, J. , Donelan-McCall, N. , & Dunn, J. (1996). Why talk about mental states? The significance of children's conversations with friends, siblings, and mothers. Child Development, 67(3), 836–849. https://doi.org/10.2307/1131864 [PubMed] [Google Scholar]
- Carlson, S. M. , Koenig, M. A. , & Harms, M. B. (2013). Theory of mind. Wiley Interdisciplinary Reviews: Cognitive Science, 4(4), 391–402. https://doi.org/10.1002/wcs.1232 [DOI] [PubMed] [Google Scholar]
- Carlson, S. M. , & Moses, L. J. (2001). Individual differences in inhibitory control and children's theory of mind. Child Development, 72(4), 1032–1053. https://doi.org/10.1111/1467-8624.00333 [DOI] [PubMed] [Google Scholar]
- Castellanos, I. , Kronenberger, W. G. , & Pisoni, D. B. (2018). Psychosocial outcomes in long-term cochlear implant users. Ear and Hearing, 39(3), 527–539. https://doi.org/10.1097/AUD.0000000000000504 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Center on the Developing Child. (2012). Executive function (In brief). http://www.developingchild.harvard.edu
- Convertino, C. , Borgna, G. , Marschark, M. , & Durkin, A. (2014). Word and world knowledge among deaf learners with and without cochlear implants. The Journal of Deaf Studies and Deaf Education, 19(4), 471–483. https://doi.org/10.1093/deafed/enu024 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cruz, I. , Quittner, A. L. , Marker, C. , & DesJardin, J. L. (2013). Identification of effective strategies to promote language in deaf children with cochlear implants. Child Development, 84(2), 543–559. https://doi.org/10.1111/j.1467-8624.2012.01863.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- de Rosnay, M. , Pons, F. , Harris, P. , & Morrell, J. (2004). A lag between understanding false belief and emotion attribution in young children: Relationships with linguistic ability and mothers' mental-state language. British Journal of Developmental Psychology, 22(2), 197–218. https://doi.org/10.1348/026151004323044573 [Google Scholar]
- DesJardin, J. L. , & Eisenberg, L. S. (2007). Maternal contributions: Supporting language development in young children with cochlear implants. Ear and Hearing, 28(4), 456–469. https://doi.org/10.1097/AUD.0b013e31806dc1ab [DOI] [PubMed] [Google Scholar]
- Diamond, A. , & Goldman-Rakic, P. S. (1989). Comparison of human infants and rhesus monkeys on Piaget's AB task: Evidence for dependence on dorsolateral prefrontal cortex. Experimental Brain Research, 74(1), 24–40. https://doi.org/10.1007/BF00248277 [DOI] [PubMed] [Google Scholar]
- Dunn, L. M. , & Dunn, D. M. (2007). Peabody Picture Vocabulary Test–Fourth Edition. Pearson Assessments. [Google Scholar]
- Ebert, S. , Peterson, C. , Slaughter, V. , & Weinert, S. (2017). Links among parents' mental state language, family socioeconomic status, and preschoolers' theory of mind development. Cognitive Development, 44, 32–48. https://doi.org/10.1016/j.cogdev.2017.08.005 [Google Scholar]
- Elliot, C. D. (2007). Differential Ability Scales–Second Edition. The Psychological Corporation. [Google Scholar]
- Fagan, M. K. , Bergeson, T. R. , & Morris, K. J. (2014). Synchrony, complexity and directiveness in mothers' interactions with infants pre- and post-cochlear implantation. Infant Behavior and Development, 37(3), 249–257. https://doi.org/10.1016/j.infbeh.2014.04.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Farkas, C. , del Real, M. T. , Strasser, K. , Álvarez, C. , Santelices, M. P. , & Sieverson, C. (2018). Maternal mental state language during storytelling versus free-play contexts and its relation to child language and socioemotional outcomes at 12 and 30 months of age. Cognitive Development, 47, 181–197. https://doi.org/10.1016/j.cogdev.2018.06.009 [Google Scholar]
- Flavell, J. H. , Everett, B. A. , Croft, K. , & Flavell, E. R. (1981). Young children's knowledge about visual perception: Further evidence for the Level 1–Level 2 distinction. Developmental Psychology, 17(1), 99–103. https://doi.org/10.1037/0012-1649.17.1.99 [Google Scholar]
- Flavell, J. H. , Flavell, E. R. , & Green, F. L. (1983). Development of the appearance-reality distinction. Cognitive Psychology, 15(1), 95–120. https://doi.org/10.1016/0010-0285(83)90005-1 [DOI] [PubMed] [Google Scholar]
- Gershon, R. C. , Wagster M. V., Hendrie H. C., Fox N. A., Cook K. F., & Nowinski C. J. (2013). NIH toolbox for assessment of neurological and behavioral function. Neurology, 80(11, Suppl. 3), S2–S6. https://doi.org/10.1212/WNL.0b013e3182872e5f [DOI] [PMC free article] [PubMed] [Google Scholar]
- Goel, V. , Grafman, J. , Sadato, N. , & Hallett, M. (1995). Modeling other minds. Neuroreport, 6(13), 1741–1746. https://doi.org/10.1097/00001756-199509000-00009 [DOI] [PubMed] [Google Scholar]
- Hall, M. L. , Eigsti, I.-M. , Bortfeld, H. , & Lillo-Martin, D. (2017). Auditory deprivation does not impair executive function, but language deprivation might: Evidence from a parent-report measure in deaf native signing children. The Journal of Deaf Studies and Deaf Education, 22(1), 9–21. https://doi.org/10.1093/deafed/enw054 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Harris, P. L. (2005). Conversation, pretense, and theory of mind. In Astington J. W. & Baird J. A. (Eds.), Why language matters for theory of mind (pp. 70–83). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195159912.003.0004 [Google Scholar]
- Holt, R. F. , Beer, J. , Kronenberger, W. G. , Pisoni, D. B. , & Lalonde, K. (2012). Contribution of family environment to pediatric cochlear implant users' speech and language outcomes: Some preliminary findings. Journal of Speech, Language, and Hearing Research, 55(3), 848–864. https://doi.org/10.1044/1092-4388(2011/11-0143) [DOI] [PMC free article] [PubMed] [Google Scholar]
- Jenkins, J. M. , Turrell, S. L. , Kogushi, Y. , Lollis, S. , & Ross, H. S. (2003). A longitudinal investigation of the dynamics of mental state talk in families. Child Development, 74(3), 905–920. https://doi.org/10.1111/1467-8624.00575 [DOI] [PubMed] [Google Scholar]
- Kronenberger, W. G. , Colson, B. G. , Henning, S. C. , & Pisoni, D. B. (2014). Executive functioning and speech-language skills following long-term use of cochlear implants. The Journal of Deaf Studies and Deaf Education, 19(4), 456–470. https://doi.org/10.1093/deafed/enu011 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kronenberger, W. G. , Pisoni, D. B. , Henning, S. C. , & Colson, B. G. (2013). Executive functioning skills in long-term users of cochlear implants: A case control study. Journal of Pediatric Psychology, 38(8), 902–914. https://doi.org/10.1093/jpepsy/jst034 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Laranjo, J. , & Bernier, A. (2013). Children's expressive language in early toddlerhood: Links to prior maternal mind-mindedness. Early Child Development and Care, 183(7), 951–962. https://doi.org/10.1080/03004430.2012.699964 [Google Scholar]
- Laranjo, J. , Bernier, A. , Meins, E. , & Carlson, S. M. (2014). The roles of maternal mind-mindedness and infant security of attachment in predicting preschoolers' understanding of visual perspective taking and false belief. Journal of Experimental Child Psychology, 125, 48–62. https://doi.org/10.1016/j.jecp.2014.02.005 [DOI] [PubMed] [Google Scholar]
- Lee, E. , & Rescorla, L. (2008). The use of psychological state words by late talkers at ages 3, 4, and 5 years. Applied Psycholinguistics, 29(1), 21–39. https://doi.org/10.1017/S0142716408080028 [Google Scholar]
- Luria, A. R. (1973). The working brain: An introduction to neuropsychology. Basic. [Google Scholar]
- Magimairaj, B. M. (2018). Parent-rating vs performance-based working memory measures: Association with spoken language measures in school-age children. Journal of Communication Disorders, 76, 60–70. https://doi.org/10.1016/j.jcomdis.2018.09.001 [DOI] [PubMed] [Google Scholar]
- McAuley, T. , Chen, S. , Goos, L. , Schachar, R. , & Crosbie, J. (2010). Is the behavior rating inventory of executive function more strongly associated with measures of impairment or executive function? Journal of the International Neuropsychological Society, 16(3), 495–505. https://doi.org/10.1017/S1355617710000093 [DOI] [PubMed] [Google Scholar]
- McMahon, C. A. , & Bernier, A. (2017). Twenty years of research on parental mind-mindedness: Empirical findings, theoretical and methodological challenges, and new directions. Developmental Review, 46, 54–80. https://doi.org/10.1016/j.dr.2017.07.001 [Google Scholar]
- Meins, E. , Fernyhough, C. , Arnott, B. , Leekam, S. R. , & de Rosnay, M. (2013). Mind-mindedness and theory of mind: Mediating roles of language and perspectival symbolic play. Child Development, 84(5), 1777–1790. https://doi.org/10.1111/cdev.12061 [DOI] [PubMed] [Google Scholar]
- Miller, J. , & Iglesias, A. (2012). Systematic Analysis of Language Transcripts (SALT), Research Version. SALT Software, LLC. [Google Scholar]
- Milligan, K. , Astington, J. W. , & Dack, L. A. (2007). Language and theory of mind: Meta-analysis of the relation between language ability and false-belief understanding. Child Development, 78(2), 622–646. https://doi.org/10.1111/j.1467-8624.2007.01018.x [DOI] [PubMed] [Google Scholar]
- Miyake, A. , Friedman, N. P. , Emerson, M. J. , Witzki, A. H. , Howerter, A. , & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41(1), 49–100. https://doi.org/10.1006/cogp.1999.0734 [DOI] [PubMed] [Google Scholar]
- Moeller, M. P. , & Schick, B. (2006). Relations between maternal input and theory of mind understanding in deaf children. Child Development, 77(3), 751–766. https://doi.org/10.1111/j.1467-8624.2006.00901.x [DOI] [PubMed] [Google Scholar]
- Morgan, G. , Meristo, M. , Mann, W. , Hjelmquist, E. , Surian, L. , & Siegal, M. (2014). Mental state language and quality of conversational experience in deaf and hearing children. Cognitive Development, 29, 41–49. https://doi.org/10.1016/j.cogdev.2013.10.002 [Google Scholar]
- Niparko, J. K. , Tobey, E. A. , Thal, D. J. , Eisenberg, L. S. , Wang, N. Y. , Quittner, A. L. , & Fink, N. E. (2010). Spoken language development in children following cochlear implantation. Journal of the American Medical Association, 303(15), 1498–1506. https://doi.org/10.1001/jama.2010.451 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Nittrouer, S. , Lowenstein, J. H. , & Antonelli, J. (2020). Parental language input to children with hearing loss: Does it matter in the end? Journal of Speech, Language, and Hearing Research, 63(1), 234–258. https://doi.org/10.1044/2019_JSLHR-19-00123 [DOI] [PMC free article] [PubMed] [Google Scholar]
- O'Meagher, S. , Norris, K. , Kemp, N. , & Anderson, P. (2019). Examining the relationship between performance-based and questionnaire assessments of executive function in young preterm children: Implications for clinical practice. Child Neuropsychology, 25(7), 899–913. https://doi.org/10.1080/09297049.2018.1531981 [DOI] [PubMed] [Google Scholar]
- Peters, K. , Remmel, E. , & Richards, D. (2009). Language, mental state vocabulary, and false belief understanding in children with cochlear implants. Language, Speech, and Hearing Services in Schools, 40(3), 245–255. https://doi.org/10.1044/0161-1461(2009/07-0079) [DOI] [PubMed] [Google Scholar]
- Pisoni, D. B. , Conway, C. M. , Kronenberger, W. G. , Henning, S. , & Anaya, E. (2010). Executive function, cognitive control, and sequence learning in deaf children with cochlear implants. In Marschark M. & Spencer P. E. (Eds.), The Oxford handbook of deaf studies, language, and education (Vol. 2, 439–457). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780195390032.013.0029 [Google Scholar]
- R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/ [Google Scholar]
- Roby, E. , & Scott, R. M. (2018). The relationship between parental mental-state language and 2.5-year-olds' performance on a nontraditional false-belief task. Cognition, 180, 10–23. https://doi.org/10.1016/j.cognition.2018.06.017 [DOI] [PubMed] [Google Scholar]
- Roy, D. (2009). New horizons in the study of child language acquisition. In Moore R. (Ed.), Proceedings of interspeech 2009 (pp. 13–20). International Speech Communication Association. [Google Scholar]
- Ruffman, T. , Slade, L. , & Crowe, E. (2002). The relation between children's and mothers’ mental state language and theory-of-mind understanding. Child Development, 73(3), 734–751. https://doi.org/10.1111/1467-8624.00435 [DOI] [PubMed] [Google Scholar]
- Sabbagh, M. A. , & Taylor, M. (2000). Neural correlates of the theory-of-mind reasoning: An event-related potential study. Psychological Science, 11(1), 46–50. https://doi.org/10.1111/1467-9280.00213 [DOI] [PubMed] [Google Scholar]
- Schick, B. , de Villiers, P. , de Villiers, J. , & Hoffmeister, R. (2007). Language and theory of mind: a study of deaf children. Child Development, 78(2), 376–396. https://doi.org/10.1111/j.1467-8624.2007.01004.x [DOI] [PubMed] [Google Scholar]
- Schumacher, A. M. , Miller, A. L. , Watamura, S. E. , Kurth, S. , Lassonde, J. M. , & LeBourgeois, M. K. (2017). Sleep moderates the association between response inhibition and self-regulation in early childhood. Journal of Clinical Child and Adolescent Psychology, 46(2), 222–235. https://doi.org/10.1080/15374416.2016.1204921 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Taumoepeau, M. , & Ruffman, T. (2006). Mother and infant talk about mental states relates to desire language and emotion understanding. Child Development, 77(2), 465–481. https://doi.org/10.1111/j.1467-8624.2006.00882.x [DOI] [PubMed] [Google Scholar]
- Taumoepeau, M. , & Ruffman, T. (2008). Stepping stones to others' minds: Maternal talk relates to child mental state language and emotion understanding at 15, 24, and 33 months. Child Development, 79(2), 284–302. https://doi.org/10.1111/j.1467-8624.2007.01126.x [DOI] [PubMed] [Google Scholar]
- Toplak, M. E. , West, R. F. , & Stanovich, K. E. (2013). Practitioner review: Do performance-based measures and ratings of executive function assess the same construct? Journal of Child Psychology and Psychiatry, and Allied Disciplines, 54(2), 131–143. https://doi.org/10.1111/jcpp.12001 [DOI] [PubMed] [Google Scholar]
- Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press. [Google Scholar]
- Wang, Y. Y. , Bergeson, T. R. , & Houston, D. M. (2017). Infant-directed speech enhances attention to speech in deaf infants with cochlear implants. Journal of Speech, Language, and Hearing Research, 60(11), 3321–3333. https://doi.org/10.1044/2017_JSLHR-H-17-0149 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wellman, H. M. , Cross, D. , & Watson, J. (2001). Meta-analysis of theory-of-mind development: The truth about false belief. Child Development, 72(3), 655–684. https://doi.org/10.1111/1467-8624.00304 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data sets generated and/or analyzed during this study are available from the corresponding author on reasonable request.