Differential At-Risk Pediatric Outcomes of Parental Sensitivity Based on Hearing Status

Abstract

Purpose

The aim of this study was to investigate the role of parental sensitivity in language and neurocognitive outcomes in children who are deaf and/or hard of hearing (DHH).

Method

Sixty-two parent–child dyads of children with normal hearing (NH) and 64 of children who are DHH (3–8 years) completed parent and child measures of inhibitory control/executive functioning and child measures of sentence comprehension and vocabulary. The dyads also participated in a video-recorded, free-play interaction that was coded for parental sensitivity.

Results

There was no evidence of associations between parental sensitivity and inhibitory control or receptive language in children with NH. In contrast, parental sensitivity was related to children's inhibitory control and all language measures in children who are DHH. Moreover, inhibitory control significantly mediated the association between parental sensitivity and child language on the Clinical Evaluation of Language Fundamentals–Fifth Edition Following Directions subscale (6–8 years)/Clinical Evaluation of Language Fundamentals Preschool–Second Edition Concepts and Following Directions subscale (3–5 years). Follow-up analyses comparing subgroups of children who used hearing aids (n = 29) or cochlear implants (CIs; n = 35) revealed similar correlational trends, with the exception that parental sensitivity showed little relation to inhibitory control in the group of CI users.

Conclusions

Parental sensitivity is associated with at-risk language outcomes and disturbances in inhibitory control in young children who are DHH. Compared to children with NH, children who are DHH may be more sensitive to parental behaviors and their effects on emerging inhibitory control and spoken language. Specifically, inhibitory control, when scaffolded by positive parental behaviors, may be critically important for robust language development in children who are DHH.

Maternal sensitivity (defined as behaviors demonstrating reliability, accessibility, and responsiveness of the mother to the child; Bowlby, 1969) is associated with a variety of developmental outcomes in children with normal hearing (NH), including language development and neurocognitive skills, such as inhibitory control (Gueron-Sela et al., 2018; Harmeyer et al., 2016; Kochanska et al., 2000; NICHD Early Child Care Research Network, 1999b, 2000, 2005; Tamis-LeMonda et al., 2001; Tiberio et al., 2016). The process by which maternal sensitivity exerts an effect on language has been of particular interest for children who are deaf and/or hard of hearing (DHH) because of potential applications in early intervention (Lam-Cassettari et al., 2015; Quittner et al., 2013). In children with NH, parental scaffolding of children's inhibitory control development has been implicated as one avenue through which maternal sensitivity might influence child language (Harmeyer et al., 2016; Pallini et al., 2018; Tiberio et al., 2016). Children who are DHH also display considerable variability (Beer et al., 2011; Botting et al., 2017; Holt, Beer, Kronenberger, & Pisoni, 2013; Kronenberger, Beer, et al., 2014; Kronenberger et al., 2020; Nicastri et al., 2020) in critical neurocognitive outcomes, including inhibitory control, that relate to language (Barker et al., 2009; Botting et al., 2017; Figueras et al., 2008; Horn et al., 2004, 2005a, 2005b; Kronenberger, Colson, et al., 2014; Kronenberger et al., 2018; Nicastri et al., 2020; Rhine-Kalback, 2004). Therefore, exploring the potential role of maternal sensitivity in the development of inhibitory control and language in children who are DHH not only has implications for understanding the interaction between one aspect of executive function (inhibitory control) and language development but also could provide a better understanding of how addressing parental sensitivity in early intervention might ameliorate some of the language delays in this clinical population. This study examined these relations in a relatively large group of children who are DHH and a control group of children with NH.

Language and Executive Functioning Development of Children Who Are DHH

Children who are DHH and communicate orally require significant early intervention and appropriate fitting of hearing technology, whether hearing aids (HAs) or cochlear implants (CIs), to achieve optimum developmental outcomes, which in many cases still lag behind those of children with NH (Friedmann & Szterman, 2011; Geers et al., 2003, 2017; Kronenberger, Beer, et al., 2014; Niparko et al., 2010; Nittrouer & Burton, 2001; Nittrouer et al., 2018). The most important of these outcomes is language development, which underlies the functioning of children who are DHH in critical areas of development and daily life, such as academics and psychosocial development (Castellanos et al., 2018; Nittrouer et al., 2012). Although the variability in language outcomes across children who are DHH has not been fully explained (Geers et al., 2003; Niparko et al., 2010), a portion of the variance in outcomes is explained by demographics and audiological factors, including age at cochlear implantation, age at first fit of HAs, and onset of early intervention (Huber & Kipman, 2012; Sininger et al., 2010; Yoshinaga-Itano, 2003).

Executive functioning (EF; the range of neurocognitive abilities that contribute to completing goal-directed behavior) has been implicated as a contributor to the language variability observed in children who are DHH (Barker et al., 2009; Botting et al., 2017; Figueras et al., 2008; Horn et al., 2004, 2005a, 2005b; Kronenberger, Colson, et al., 2014; Kronenberger et al., 2018; Nicastri et al., 2020; Rhine-Kalback, 2004). Similar to language outcomes, EF abilities in children who are DHH also demonstrate considerable unexplained variability (Beer et al., 2011; Botting et al., 2017; Holt, Beer, Kronenberger, & Pisoni, 2013; Kronenberger, Beer, et al., 2014; Kronenberger et al., 2020; Nicastri et al., 2020; Rhine-Kalback, 2004). Children who are DHH, whether using HAs or CIs, have reduced auditory input, spoken language access, and daily communication compared to their NH peers (Akhtar et al., 2001). The accumulation of these lost opportunities to hear, encode, and engage in this time-varying signal—spoken language—is hypothesized to negatively influence neural organization and neurocognitive development that is auditory and language dependent, including inhibitory control (Conway et al., 2009; Kral et al., 2016). Inhibitory control is a primary subdomain of EF that involves withholding initial impulsive responses in order to anticipate outcomes and control behavior (Carlson & Moses, 2001; Kochanska et al., 1997; Rothbart et al., 1994). Inhibitory control is hypothesized to contribute to typical language development in a transactional and bidirectional manner (Bernier et al., 2010; Gooch et al., 2016; Harmeyer et al., 2016) by optimizing language learning during sequential exposure to linguistic experiences (Blair & Razza, 2007; Fuhs et al., 2014; Raver et al., 2011) and by using language to proactively regulate impulsive behaviors with internal representations managed by top-down executive function processes (Bernier et al., 2010; Doebel & Zelazo, 2016; Vygotsky, 1986). This typical developmental process can be disrupted by both language and neurocognitive deficits in children who are DHH.

A growing body of research offers evidence for a role of the inhibitory control subdomain of EF for language development in people who are DHH. Language is more effortful and less automatic and, therefore, requires more controlled-sustained attention in children who are DHH than in children with NH (Grieco-Calub et al., 2009; Nittrouer & Burton, 2001). A recent investigation builds on this previous research in children who are DHH by suggesting that available EF may contribute to language functioning by providing effortful cognitive control for processing challenging or complex linguistic stimuli (Kronenberger et al., 2018). Two complementary theories of language processing, the Ease of Language Understanding theory (Rönnberg et al., 2013) and the Framework for Understanding Effortful Listening (Pichora-Fuller et al., 2016), invoke the role of working memory, a subdomain of EF in effortful listening. Working memory involves the activation of executive control processes, including inhibitory control (to resist impulses and distractions), in order to retain memory contents during concurrent/competing cognitive processing (Barkley, 2012). Thus, other EF processes, including inhibitory control, are hypothesized to interact with working memory in effort-based language processing (Kronenberger et al., 2018). The role and utilization of these other EF skills, such as inhibitory control, in effortful listening situations have received some preliminary support but require further investigation (Kronenberger & Pisoni, 2020). However, both theories suggest a need for the activation of additional effort-based resources (stemming from EF) for listening and language processing in people with hearing loss, because of the inherently degraded auditory input received from hearing devices and impaired auditory systems. In other words, even quiet listening environments void of auditory distractions can be challenging for listeners who are DHH, requiring additional resources to successfully comprehend and engage in spoken language communication (Pichora-Fuller et al., 2016; Rönnberg et al., 2013). One aspect of EF that likely contributes to this inherent effortful listening experienced by listeners who are DHH is inhibitory control, because it requires the development of sustained levels of attention and controlled responses.

Although theoretically important and relevant for language development, investigations of inhibitory control specifically, independent of other aspects of EF, in children who are DHH have been limited; the expression, association, and mechanism of inhibitory control in relation to language development require further investigation. In children who are DHH who use CIs, inhibitory control has repeatedly been observed to be delayed or deficient relative to children with NH (Barker et al., 2009; Beer et al., 2011, 2014; M. Hoffman et al., 2018; Holt, Beer, Kronenberger, & Pisoni, 2013; Horn et al., 2005b; Khan et al., 2005; Kronenberger, Colson, et al., 2014; Kronenberger et al., 2013, 2020; Sporn, 1997). A recent study showed lower inhibitory control on both performance- and questionnaire-based measures of inhibitory control in children who are DHH (Kronenberger et al., 2020). Moreover, in children with CIs, inhibitory control has been related to language (Barker et al., 2009; Botting et al., 2017; Figueras et al., 2008; Horn et al., 2004, 2005a, 2005b; Kronenberger, Colson, et al., 2014; Nicastri et al., 2020).

Examination of inhibitory control in children who use HAs has been more limited, but investigators have also found poorer inhibitory control relative to children with NH when children with HAs are combined with children with CIs (Botting et al., 2017) and when examined separately (Bell et al., 2020; Figueras et al., 2008; Khan et al., 2005; Mitchell & Quittner, 1996; Quittner et al., 1994). An early study examined the results of a continuous performance test (CPT) measuring selective attention; the aspect of the CPT associated with response inhibition—rate of commissions—occurred significantly more in children who use HAs than their peers with NH (Mitchell & Quittner, 1996). One study compared children with HAs, CIs, and NH separately, revealing that children with HAs and CIs had poorer performance on a sustained attention task than children with NH (Khan et al., 2005). Bell et al. (2020) evaluated inhibitory control in three groups of children: those with HAs, those with attention-deficit/hyperactivity disorder (ADHD), and neurotypical children with NH. Comparable abilities in response inhibition were found in children with HAs and those with ADHD; both groups' response inhibition was significantly reduced relative to neurotypical children with NH. Importantly, the results implicated different neural activation patterns in all three groups during the same response inhibition task, supporting differences in children with HAs relative to their peers with NH in neural organization and performance ability in inhibitory control (Bell et al., 2020). Only two studies have examined and found a relation between inhibitory control and spoken language in children with HAs, both of which combined children with HAs and children with CIs into a single group for this analysis (Botting et al., 2017; Figueras et al., 2008).

Parental Sensitivity, Language, and EF Development in Children Who Are DHH

Although EF and language are closely intertwined in child development, neither fully explains the development or outcome of the other; rather, a complex interplay of biological, psychological, and social factors interacts to influence neurocognitive and spoken language outcomes in children who are DHH (Kronenberger & Pisoni, 2020). Within this complex interplay of systems affecting language development, a primary influence is likely to be the family system. The social-behavioral risk model (Holt et al., 2020) applies systems theory (Kazak 1989) to identify the developmental outcome effects of social relationships in children who are DHH, the most proximal and impactful of which is the immediate family (Kazak, 1992).

One critical component of family environment that has been demonstrated to influence language outcome in samples of children who are DHH is parental sensitivity (Pressman et al., 1999; Quittner et al., 2013). Parental sensitivity is a construct that is composed of consistent, appropriate, and timely awareness and behavior in parent–child interactions (Ainsworth et al., 1978) and is primarily assessed by observing and rating the quality and quantity of parental behaviors in parent–child interaction that are appropriate, cognitively stimulating, and affectively engaging (Biringen & Robinson, 1991). Parental behaviors measured in this way have been found to be associated with both language and inhibitory control in children with NH (Gooch et al., 2016; Merz et al., 2017; Tiberio et al., 2016), possibly because parental sensitivity provides scaffolding for children's internalization of self-regulatory behaviors and inhibitory control skills (Harmeyer et al., 2016; Pallini et al., 2018; Tiberio et al., 2016). The resulting improvement in inhibitory control abilities is thought to increase children's sustained, goal-directed behavior and their ability to actively learn, attend, and retain information from their surroundings, specifically in the area of language development (Blair & Razza, 2007; Fuhs et al., 2014; Raver et al., 2011). An alternative mechanism argues that parental sensitivity promotes language development by providing enriched language input and a secure base for exploration with appropriate and attentive guiding of children's abilities and in-the-moment difficulties (Dave et al., 2018; Madigan et al., 2019; Vallotton et al., 2017). These two proposed mechanisms highlight the inherent bidirectional interplay between inhibitory control and language development.

Studies of parental sensitivity and language in children who are DHH have been relatively sparse, and there are no known studies on the relations between parental sensitivity and inhibitory control in children who are DHH. The communicative behaviors of parents of children who are DHH have been examined in domains ranging from gestures and speech during infancy to affective and communicative behaviors in childhood (Quittner et al., 2013, 2016; Pressman et al., 1999; Roberts & Hampton, 2018; Wang et al., 2017). Positive parental behaviors, when displayed as parental sensitivity, responsivity, or gestures, have positive effects on later language of children who are DHH (Pressman et al., 1999; Quittner et al., 2013; Roberts & Hampton, 2018).

Some limited findings suggest that parental behaviors might be related to inhibitory control in children who are DHH. Specifically, maternal depression has been associated with poorer inhibitory control in children who are DHH (Shin et al., 2007) and less frequent displays of sensitivity/responsiveness in family interactions (Y. Hoffman & Drotar, 1991). Additionally, negative familial behaviors such as excessive control and conflict are associated with poorer child inhibitory control (Holt, Beer, Kronenberger, & Pisoni, 2013). Positive familial behaviors such as cohesion and expressiveness were associated with better child inhibitory control (Holt et al., 2020). A recent study from our lab has examined parenting stress, revealing that although parenting stress levels were not significantly different between parents of children with NH or who are DHH, there was a significant negative relation between parenting stress and child inhibitory control for children who are DHH that was indirectly accounted for by delayed language comprehension skills (Blank et al., 2020). Parenting stress levels are also inversely related to sensitive parental behaviors (Alquraini et al., 2019; Unternaehrer et al., 2019). Together, these studies suggest that parental behaviors related to sensitivity might be an important source of individual differences in language and inhibitory control outcomes, particularly in children who are DHH, who are at greater risk for negative outcomes in both of these domains.

Study Purpose

In order to investigate the role of parental sensitivity in language and neurocognitive outcomes in children who are DHH, this study sought to address two primary aims: (a) to examine the relation between parental sensitivity, child language skills, and child inhibitory control and (b) to investigate whether the association between parental sensitivity and child inhibitory control mediates the effect of parental sensitivity on child language. It was expected that greater levels of parental sensitivity would promote better child language by enhancing the child's emerging inhibitory control in both samples of children with NH or who are DHH, but that the presence and strength of this effect would be greater in the group of children who are DHH.

Method

Participants

Two groups of parent–child (3–8 years of age) dyads participated in this investigation: 62 children with NH and 64 children who are DHH who used HAs (n = 29) or CIs (n = 35). Participants were recruited serially as part of a larger longitudinal study examining the role of family environment on outcomes in children with hearing loss. Fifty-eight of the caregivers from the group of children with NH were mothers (four were fathers), and 57 of the caregivers from the group of children who are DHH were mothers (including six who were adoptive mothers), four were fathers, and three were grandmothers.

Inclusion/Exclusion Criteria

Parents were required to have reported NH and English as their primary language. Children were required to score within 2 SDs below the mean (T score > 30) or higher on the Differential Ability Scales–Second Edition Picture Similarities subtest (Elliot, 2007), a measure of nonverbal ability, and to have no history of any developmental disabilities/delays (other than known sequelae of hearing loss in the sample of children who are DHH). In addition, children with NH were required to pass a bilateral behavioral hearing screening at 25 dB HL at octave frequencies between and including 250–4000 Hz (re: American National Standards Institute, 2010). The screening was administered by researchers in the families' homes using an Earscan 3 handheld screening audiometer with insert earphones (Micro Audiometrics Corp., 2018). The children who are DHH were identified with hearing loss and received intervention with amplification before 2 years of age. The children with CIs were implanted before 3.5 years of age. All children who are DHH and their families had the goal of acquiring spoken language, listening, and speaking skills.

Table 1 displays a summary of participant demographic characteristics. Independent-samples t tests for continuous data, Mann–Whitney U tests for ordinal data, and Pearson chi-square analyses for categorical data were carried out to compare participant demographics between groups. The HA users and the CI users only differed from each other in unaided (at identification of hearing loss) four-frequency pure-tone average (PTA; 0.5, 1, 2, and 4 kHz), t(48) = −7.89, p < .001 (CI users had higher PTAs, as expected). Therefore, the HA and CI users were combined into a single group of children who are DHH to increase power in the target analyses. Children with NH or who are DHH did not differ on child gender, χ²(1) = 1.55, p = .213, mean household income, Mann–Whitney U = 1.89, p = .059, or child age, t(124) = −1.37, p = .174. The parents of children with NH had significantly higher levels of education than the parents of children who are DHH, Mann–Whitney U = 2.36, p = .018.

Table 1.

Participant demographics and hearing history by hearing group.

Characteristics	NH	DHH (HA and CI)	HA	CI
	M (SD)	M (SD)	M (SD)	M (SD)
n	62	64	29	35
No. of males/females	34/28	28/36	12/17	16/19
Chronological age, child (years.)	6.0 (1.6)	6.4 (1.6)	6.3 (1.7)	6.4 (1.5)
Parental education a	8.1* (1.3)	7.6* (1.3)	7.8 (1.2)	7.5 (1.3)
Annual family income b	8.8 (1.6)	7.8 (2.6)	8.6 (2.0)	7.3 (2.8)
Race distribution (n)
White/Caucasian	44	49	21	28
Asian	1	4	2	2
Black/African American	1	4	2	2
More than 1 race	16	7	4	3
Audiological characteristics
Hearing age (years) c	n/a	6.0 (1.6)	5.4 (1.9)	4.9 (1.6)
Unaided 4-frequency PTAd (dB HL)	n/a	70.3 (26.1)	50.9*** (14.1)	89.7*** (20.1)
Aided 4-frequency PTA e (dB HL)	n/a	23.2 (7.3)	21.1 (9.8)	24.0 (6.0)

Note. n = number of participants; NH = normal hearing; DHH = deaf and/or hard of hearing; HA = hearing aid; CI = cochlear implant; PTA = pure-tone average. re: American National Standards Institute (2004); n/a = not applicable.

^a Parental education was coded based on levels of formal education: 1 = elementary school, 2 = junior high/middle school, 3 = some high school, 4 = General Education Development (GED)/high school equivalency, 5 = high school diploma, 6 = technical/vocational school, 7 = associate degree/some college, 8 = bachelor's degree, 9 = master's degree, 10 = doctorate degree.

^b Parents indicated their annual income from the following income brackets: 1 = under $5,000, 2 = $5,000–$9,999, 3 = $10,000–$14,999, 4 = $15,000–$24,999, 5 = $25,000–$34,999, 6 = $35,000–$49,999, 7 = $50,000–$64,999, 8 = $65,000–$79,999, 9 = $80,000–$94,999, 10 = $95,000 and over.

^c Calculated by subtracting age at which child was first fit with HAs or CIs from their chronological age.

^d Calculated at 0.5, 1, 2, and 4 kHz in the better ear based on data from 50 children (25 HA and 25 CI users, respectively) due to lack of access to the medical information.

^e Calculated at 0.5, 1, 2, and 4 kHz in the better ear based on data from 39 children (11 HA and 28 CI users, respectively) due to lack of access to the medical information.

^* p < .05.

^*** p < .001.

Parental education level is related to parental sensitivity in both children with NH and those who are DHH (Newton et al., 2014; Pressman et al., 1999; Quittner et al., 2013). It is also often used as a proxy for a number of related factors, including family household income and socioeconomic status (Liberatos et al., 1988; Neuhauser, 2018). The relation of this demographic variable to child outcomes is also hypothesized to serve as an indicator of parental behaviors, such as parental time investment with children and higher cognitive and social resources leading to more sensitive interactions (Del Boca et al., 2016; Del Bono et al., 2016; Neuhauser, 2018). Examining factors both modifiable in intervention and theoretically related to child outcomes of interest and potential mechanisms of action led to the investigation of parental sensitivity. Based on its potential relation to parental sensitivity and child outcome variables, parental education was controlled for in mediation analyses.

Materials

Video-Recorded Dyadic Play Interaction: Parental Sensitivity

Parent–child dyads completed a 20-min play interaction with standard sets of five age-appropriate toys. The play interaction was video-recorded with a GoPro HERO4 video camera, and parent and child utterances were fed to the video camera via Audio-Technica ATW-T1801 or 1701/L transmitters with an omnidirectional lavalier microphone. Clinical researchers monitored the play from a separate room and only interrupted the recording if the dyad left the recording frame for more than a few seconds (to reframe the shot or encourage participants to reenter the frame).

Parental behaviors during the play interactions were coded along 23 scales for parental, child, and dyadic behavior using an observational coding strategy based on the National Institutes of Child Health and Human Development coding scales (NICHD Early Child Care Research Network, 1997, 1999a, 2000) that were further developed and extended for use by the Connecticut Early Development Project (Sosinsky et al., 2004). Our team revised the manual (which was originally intended for children under 4 years of age) to include age-appropriate behaviors for each scale across the age range included in this study (3–8 years of age). Each scale was scored on an ordinal scale from 1 (behavior was low in both frequency and intensity) to 7 (behavior was high in both frequency and intensity). The Parental Sensitivity Scale utilized for this project was defined as “child-centered behavior resulting from an accurate perception of the child's mental state” (Sosinsky et al., 2004, p. 5). Behaviors that apply to this scale (as described in our revised manual) may include contingent, topical responses to child communicative speech or behaviors; the parent checking in visually with child during play; warm, appropriate, and affective communication; facilitating but not overcontrolling a child's play; and providing an appropriate level of stimulation and range of activities.

Two coders were extensively trained on the coding strategy using 13 training videos from a previous study using a similar procedure with children with NH and who are DHH (Holt, Beer, Kronenberger, Pisoni, Smith, & Lalonde, 2013). Interrater reliability for the training videos was assessed for each scale using two-way random intraclass correlation (ICC) values (see Appendix Table A1). After training and while coding study videos, coders met to discuss difficult videos with the primary author every week. Of the total 126 videos, 25% were double-coded to assess both interrater reliability and rater drift from original training reliability (see Appendix Table A2); the remaining 75% of the videos were coded by only one coder. The ICC value on the test videos for Parental Sensitivity Scale, the scale used here, was .725, indicating that the raters were reliable (Koo & Li, 2016).

Receptive Language

Child receptive language was evaluated with three measures. Receptive vocabulary was assessed with the Peabody Picture Vocabulary Test–Fourth Edition (PPVT-4; Dunn & Dunn, 2007), which measures the ability of the child to identify a picture matching a word spoken by the examiner. Receptive sentence comprehension was assessed with the Comprehensive Assessment of Spoken Language, Second Edition (CASL-2; Carrow-Woolfolk, 2017) Sentence Comprehension subtest. This subtest of the CASL-2 assesses recognition of different sentence types, clause constructions, word order, and grammatical structures from semantically similar picture response options. The Clinical Evaluation of Language Fundamentals–Fifth Edition (CELF-5; Semel et al., 2013) Following Directions subtest (for participants 6–8 years of age) and the Clinical Evaluation of Language Fundamentals Preschool–Second Edition (CELF Preschool-2; Wiig et al., 2004) Concepts and Following Directions subtest (for participants 3–5 years of age) were used to assess receptive sentence comprehension of shapes, colors, and spatial directions of increasing length and complexity.

Inhibitory Control

The iPad-based National Institutes of Health Toolbox Flanker Inhibitory Control and Attention Test (NIH Flanker; Gershon et al., 2013) was used to assess inhibitory control for both children and parents. Participants are instructed to press a button on the screen that matches the direction indicated by an arrow (or a fish, for young children) in the center of an array of distractors. On a given trial, the middle arrow is either pointing at the same direction as the other arrows (congruent) or at the opposite direction of the other arrows (incongruent). To demonstrate inhibitory control, the prepotent dominant response of pressing the button corresponding to the direction of the majority of the arrows must be overcome in order to perform the secondary, effortful response of pressing the button that corresponds to the direction of the middle arrow only. Accuracy and reaction time on incongruent trials are measured as components of a calculated standard score.

This task was chosen because it is well normed across development, does not require a verbal response (important for assessments of participants with hearing loss; Schum, 2004), and was validated with other performance-based measures of inhibition (Zelazo et al., 2013, 2014). Flanker tasks (Eriksen & Eriksen, 1974) have been validated as measures of inhibitory control and of aspects of executive attention and interference control, two constructs encompassing the more general cognitive control ability underlying much of EF (Fan et al., 2002; Paap et al., 2019). Some studies have suggested that flanker-type tasks are task-specific and not significantly correlated with questionnaires of self-control/impulsivity (Paap et al., 2020). Questionnaire measures are alternatives to performance-based measures that often assess behaviors associated with self-control and impulsivity. One commonly used questionnaire in the population of children who are DHH, the Behavior Rating Inventory of Executive Function (BRIEF-2; Gioia et al., 2015), has been suggested to be related to behavioral disruption and impairment in EF, rather than relative levels of inhibitory control ability (McAuley et al., 2010). In this study, a performance-based task with good validity relating to cognitive control was selected in order to have a continuous-scaled assessment of inhibitory control ability, consistent with study hypotheses of the nature of scaffolding ability of parental sensitivity in relation to child inhibitory control. In previous research in our laboratory (Blank et al., 2020), the NIH Flanker was used in similar analyses to examine the relation of parental stress with inhibitory control and child language; this study is a logical extension of parenting stress into parental sensitivity behaviors.

Procedure

Parents completed a demographic questionnaire prior to researchers visiting the families' homes to administer in-person assessments. Visits lasted up to 2.5 hr in length. During the home visit, one clinical researcher administered child assessments, while the other worked with the parent (only a subset of the assessments is reported on here). At the end of the visit, the child and parent completed the video-recorded dyadic play interaction.

Statistical Analysis

Statistical analyses were performed using IBM SPSS v.24/v.26 (2016/2019; IBM Corp.); all p values are two-tailed. First, the groups of children with NH and those who are DHH were compared on parental sensitivity, language, and inhibitory control measures using independent-samples t tests. Pearson correlations were performed separately by hearing group between parental sensitivity, language, and child inhibition scores. A total of six mediation analyses were carried out for each hearing group independently for each receptive language measure using the PROCESS macro (Hayes, 2018; Hayes & Rockwood, 2017). Evidence of mediation is obtained through a significance test of the indirect effect (e.g., βi coefficient), which, statistically, is composed of the product of the effect of the hypothesized causal variable (parental sensitivity) on the mediator (Child NIH Flanker; e.g., βa coefficient) and the effect of the mediator on the outcome variable (child receptive language measure; e.g., βb coefficient) while controlling for the causal variable (parental sensitivity). A bootstrapped distribution of the indirect effect was generated with 10,000 resamplings and tested with a 95% confidence interval expressing the likelihood that the indirect effect is present 95% of the time in these data. Parental NIH Flanker, parental education level, and child age were statistically controlled in all mediation analyses. Correlation and mediation analyses were repeated within the group of children who are DHH, separated by HA users and CI users, to investigate possible differences between these two subgroups of children with hearing loss.

Results

Comparative Analyses

Table 2 displays the descriptive statistics for parental sensitivity, NIH Flanker, and child receptive language. Parents of children with NH or who are DHH did not differ on ratings of parental sensitivity, t(124) = 0.098, p = .922, or NIH Flanker, t(124) = −0.0410, p = .968. As expected, children with NH had significantly better performance than children who are DHH on the PPVT-4, t(103) = 8.45, p < .001; the CASL-2, t(113) = 3.67, p < .001; the CELF-5/CELF Preschool-2, t(124) = 4.65, p < .001; and the NIH Flanker, t(124) = 3.41, p = .001.

Table 2.

Group means (standard deviations) of parent and child assessments of sensitivity, receptive language, and inhibitory control.

Measure name	NH	DHH
Parent measures
Parental Sensitivity	5.0 (1.0)	5.0 (0.9)
NIH Flanker	89.9 (12.1)	90.0 (14.1)
Child measures
PPVT-4	117.0*** (10.3)	96.0*** (17.3)
CASL-2	112.0*** (11.7)	103.0*** (16.6)
CELF-5/CELF Preschool-2	10.7*** (2.9)	8.1*** (3.4)
NIH Flanker	101.0** (12.7)	92.0** (15.9)

Note. NH = normal hearing; DHH = deaf and/or hard of hearing; NIH Flanker = National Institutes of Health Toolbox Flanker Inhibitory Control and Attention Test, results given in standard scores; PPVT-4 = Peabody Picture Vocabulary Test–Fourth Edition, results given in standard scores; CASL-2 = Comprehensive Assessment of Spoken Language, Second Edition Sentence Comprehension subtest, results given in standard scores; CELF-5/CELF Preschool-2 = Clinical Evaluation of Language Fundamentals–Fifth Edition/Clinical Evaluation of Language Fundamentals Preschool–Second Edition, results given in scaled scores (children ages 6–8 years were assessed using the Following Directions subtest from the CELF-5 and children ages 3–5 years were assessed using the Concepts and Following Directions subtest for the CELF Preschool-2).

^** p < .01.

^*** p < .001.

Correlation Analyses

Table 3 displays the correlation matrices for parental sensitivity, child language, and child inhibitory control scores for both groups. In the NH sample, only two correlations were statistically significant (PPVT-4 with CASL-2 and NIH Flanker with CASL-2). In contrast, in the sample of children who are DHH, all correlations between variables were significant. Notably, the three language measures were very strongly correlated in the sample of children who are DHH, which was expected because all these measures assess language ability and performance. Parental sensitivity was significantly correlated with the child language and inhibitory control measures in the sample of children who are DHH.

Table 3.

Correlations between measures of parental sensitivity, receptive language, and inhibitory control by hearing group.

Variables	1.	2.	3.	4.	5.
Children with NH
1. Parental Sensitivity	—
2. PPVT-4	−.166	—
3. CASL-2	−.235	.285*	—
4. CELF-5/CELF Preschool-2	−.030	.200	.145	—
5. Child NIH Flanker	0.101	−.065	.265*	.193	—
Children who are DHH
1. Parental Sensitivity	—
2. PPVT-4	.398**	—
3. CASL-2	.269*	.721***	—
4. CELF-5/CELF Preschool-2	.242*	.807***	.699***	—
5. Child NIH Flanker	.259*	.341**	.355**	.421**	—

Note. Results are given in bivariate Pearson correlation coefficients. NH = normal hearing; PPVT-4 = Peabody Picture Vocabulary Test–Fourth Edition; CASL-2 = Comprehensive Assessment of Spoken Language, Second Edition Sentence Comprehension subtest; CELF-5/CELF Preschool-2 = Clinical Evaluation of Language Fundamentals–Fifth Edition/Clinical Evaluation of Language Fundamentals Preschool–Second Edition (children ages 6–8 years were assessed using the Following Directions subtest from the CELF-5 and children ages 3–5 years were assessed using the Concepts and Following Directions subtest for the CELF Preschool-2); NIH Flanker = National Institutes of Health Toolbox Flanker Inhibitory Control and Attention Test; DHH = deaf and/or hard of hearing.

^* p < .05.

^** p < .01.

^*** p < .001.

Mediation Analyses

Six bootstrap confidence interval mediation analyses were conducted (see Figure 1)—one for each of the three receptive language outcome measures in each hearing group. Results for the children with NH are displayed in the top panel, and results for the children who are DHH are displayed in the bottom panel. Effect estimates are given in standardized (Z-transformed) coefficients. In the group of children with NH, there were no significant indirect effects detected by a 95% confidence interval. In the group of children who are DHH, one significant indirect effect was found for the language outcome variable CELF-5/CELF Preschool-2 (βi = 0.099, 95% confidence interval [0.003, 0.221]).

Figure 1.

Top: Mediation analyses results for children with normal hearing (NH). Bottom: Mediation analyses results for children who are deaf and/or hard of hearing (DHH). βa = estimate of the effect of parental sensitivity on the mediator measure, the National Institutes of Health Toolbox Flanker Inhibitory Control and Attention Test (Child NIH Flanker), given in a standardized (Z-transformed) coefficient; βi = estimate of the indirect effect of parental sensitivity on each language outcome measure, given in standardized (Z-transformed) coefficients; 95% CI = 95% confidence interval that contains βi; βb = standardized estimate of the effect of the mediator, Child NIH Flanker, on each language outcome measure, given in standardized (Z-transformed) coefficients; PPVT-4 = Peabody Picture Vocabulary Test–Fourth Edition; CASL-2 = Comprehensive Assessment of Spoken Language, Second Edition Sentence Comprehension subtest; CELF-5/CELF Preschool-2 = Clinical Evaluation of Language Fundamentals–Fifth Edition/Clinical Evaluation of Language Fundamentals Preschool–Second Edition (children ages 6–8 years were assessed using the Following Directions subtest from the CELF-5 and children ages 3–5 years were assessed using the Concepts and Following Directions subtest for the CELF Preschool-2). *p < .05, **p < .01.

Within-Group Analyses

To further examine if children with HAs and those with CIs might differ from each other in how parental sensitivity is related to child language and inhibitory control, equivalent correlation and mediation analyses on these two subgroups were carried out (see Table 4). The results differ for both subgroups from Table 3 in which both groups were collapsed into a larger group of children who are DHH in that not all of the relations remained significantly correlated for either subgroup. The children with HAs showed fewer correlations reaching significance than those with CIs, and on average, the correlations that were significant were slightly stronger in those with CIs than those with HAs. Still, both subgroups had significant, positive correlations between parental sensitivity and child language. The group of children who use HAs still showed a significant relation between parental sensitivity and child inhibitory control, r(27) = .496, p = .006. The relation between parental sensitivity and the NIH Flanker in the CI group showed the largest decrease in correlation coefficient size relative to the combined group of children who are DHH. None of the indirect effects in either the HA or CI group mediation analyses were significant.

Table 4.

Correlations between measures of parental sensitivity, receptive language, and inhibitory control by hearing device used.

Variables	1.	2.	3.	4.	5.
Children with HAs
1. Parental Sensitivity	—
2. PPVT-4	.413*	—
3. CASL-2	.126	.616***	—
4. CELF-5/CELF Preschool-2	.150	.740***	.534**	—
5. Child NIH Flanker	.496**	.358	.286	.335	—
Children with CIs
1. Parental Sensitivity	—
2. PPVT-4	.410*	—
3. CASL-2	.382*	.807***	—
4. CELF-5/CELF Preschool-2	.317	.839***	.807***	—
5. Child NIH Flanker	.044	.277	.393*	.460**	—

Note. Results are given in bivariate Pearson correlation coefficients. HAs = hearing aids; PPVT-4 = Peabody Picture Vocabulary Test–Fourth Edition; CASL-2 = Comprehensive Assessment of Spoken Language, Second Edition Sentence Comprehension subtest; CELF-5/CELF Preschool-2 = Clinical Evaluation of Language Fundamentals–Fifth Edition/Clinical Evaluation of Language Fundamentals Preschool–Second Edition (children ages 6–8 years were assessed using the Following Directions subtest from the CELF-5 and children ages 3–5 years were assessed using the Concepts and Following Directions subtest for the CELF Preschool-2); NIH Flanker = National Institutes of Health Toolbox Flanker Inhibitory Control and Attention Test; CIs = cochlear implants.

^* p < .05.

^** p < .01.

^*** p < .001.

Discussion

This study investigated associations between parental sensitivity, child language skills, and child inhibitory control in children who are DHH and a control group with NH. The study also tested a theoretical model in which inhibitory control mediates the effect of parental sensitivity on child language in children who are DHH. Consistent with hypotheses suggested by studies on children with both typical development (Blair & Razza, 2007; Fuhs et al., 2014; Raver et al., 2011), as well as information and language processing theories (e.g., Kronenberger & Pisoni, 2019; Kronenberger et al., 2020) stemming from developmental theories of children who are DHH (Conway et al., 2009; Kral et al., 2016), we found significant associations between parental sensitivity, child inhibitory control, and child language development in the sample of children who are DHH, which were much stronger than the associations found in the sample of children with NH. Furthermore, for the CELF-5/CELF Preschool-2 (the measure of spoken language comprehension), child inhibitory control mediated the association between parental sensitivity and child language, even after statistically controlling for parental inhibitory control skills and parental education. Whereas prior work has shown an association between parental sensitivity and language outcomes in children who are DHH (Pressman et al., 1999; Quittner et al., 2013), this is the first study to demonstrate that the association between parental sensitivity and child language is larger in children who are DHH than in their peers with NH and that an association exists between parental sensitivity and child inhibitory control in children who are DHH. Moreover, this study found preliminary support in a sample with somewhat limited statistical power that inhibitory control mediates the association between parental sensitivity and language comprehension in children who are DHH, even after accounting for the parent's own inhibitory control skills and education level.

When the group of children who are DHH was subdivided and reanalyzed in subgroups of children who use HAs or CIs, correlations were attenuated for several analyses compared to correlations obtained for the combined DHH sample, although the majority of correlations remained statistically significant and in the predicted direction. Furthermore, in mediation analyses, no significant indirect effects were found for either subgroup. Separation of the DHH sample into subsamples significantly reduced the sample size for each analysis, limiting the statistical power to detect small-to-medium effect sizes. This attenuation of statistical power from dividing the DHH sample was particularly substantial for the mediation analyses, which require larger sample sizes for an adequate test of mediation effects (Kenny & Judd, 2014). What these results do show, however, is that parental sensitivity has relations with child language in both groups of children, a novel finding for children with HAs, suggesting some overlap in the audiological experiences and potential needs of children who use HAs or CIs in relation to parental sensitivity. Children who use HAs are an understudied clinical population in general (Donahue, 2007), but especially in terms of measures of parental sensitivity and inhibitory control. These intragroup analyses offer some preliminary evidence for the importance of parental sensitivity underlying language outcomes for children who are DHH regardless of device use and do not appear to sug[gest that one subgroup is responsible for the differences found between children who are DHH and those with NH.

The low correlation between parental sensitivity and NIH Flanker in the group of children with CIs should be further investigated, as it could suggest a potential divergence between children who use CIs versus HAs in the mediation of the parental sensitivity–language association by inhibition. It is possible that children who use CIs, who typically have more extreme hearing loss and subsequent interventions, have differing neurocognitive development and neural activation pathways in relation to inhibition than children who use HAs. This could result in inhibitory control delays of children who use CIs that are less malleable to the effects of parental sensitivity compared to children who use HAs. Alternatively, the nature of inhibitory control difficulties for a child with CIs may not align with typical expressions of sensitivity from a parent; research into parental sensitivity in children with severe-to-profound hearing loss have found that those parents use more directives and intrusive behaviors in interaction (Lam-Cassettari et al., 2015; Meadow-Orlans, 1997; Paradis & Koester, 2015), although some emerging evidence suggests that this may be due to the parents adjusting their interactions to address the greater communication needs of their children (Fagan et al., 2014; Kondaurova & Bergeson, 2011; Kondaurova et al., 2013, 2015; N. A. Smith & McMurray, 2018). This could lead to a lack of relation between coded “positive” behaviors of parental sensitivity and higher inhibitory control outcomes in children with CIs. Further investigation and replication of this association and possible explanatory factors are needed.

In the sample of children who are DHH, parental sensitivity was related directly to receptive language on the PPVT-4, the CASL-2, and the CELF-5/CELF Preschool-2, and was related indirectly to child language through the child's inhibitory control ability for the CELF-5/CELF Preschool-2 after accounting for other contributors to child language development (parental education level, parent inhibitory control, and child age). In children with NH, we did not find any evidence that parental sensitivity impacts child language through children's inhibitory control skills or otherwise for the measures used in this investigation. These results are consistent with several recent accounts of auditory access for children who are DHH (Conway et al., 2009; Kral et al., 2016) and expand the scope of the role of EF in current theories of information and language processing, such as the Ease of Language Understanding theory (Rönnberg et al., 2013) and the Framework for Understanding Effortful Listening (Pichora-Fuller et al., 2016), by adding inhibitory control to working memory as core EF components that are activated to support listening effort and to compensate for hearing and language delays. This study extends previous research linking inhibitory control and language in children who are DHH (Botting et al., 2017; Figueras et al., 2008; Horn et al., 2004, 2005a, 2005b; Kronenberger, Colson, et al., 2014; Kronenberger et al., 2018) by providing preliminary evidence for a family-based mechanism of action between DHH child inhibitory control and their language: the relation between child inhibitory control and parental sensitivity. In addition, specific to children who are DHH, recent research has proposed that, relative to peers with NH, spoken language development in children who are DHH who receive HAs or CIs is more dependent on other sources of variability, including parent–child linguistic interactions (Kronenberger & Pisoni, 2019; Kronenberger et al., 2020). In contrast, because children with NH typically acquire spoken language with a greater use of fast automatic phonological and semantic linguistic processing channels, their language development may be more resilient in the face of variability in environmental influences, such as differences in parental behaviors in the form of parental sensitivity (G. N. L. Smith et al., 2019).

Alternatively, parental sensitivity may have a disproportionally high impact on language development in children who are DHH because these children have more to gain from environmental variation than children with NH as a result of their significant early language delays. A prior novel investigation demonstrates that language growth in children who are DHH with CIs occurs, particularly at preschool and early school ages, at a faster rate than that of their peers with NH (Kronenberger et al., 2020). The sensitivity of this period of rapid developmental change was reported by another recent study by Nittrouer et al. (2020), who found a similar pattern of results using a different methodology with younger children than were included in this study. Language development of preschool-age children with NH was largely “resilient” (p. 234) to parental language input, whereas language scores of children who are DHH (with HA users and CI users divided into separate groups) both demonstrated significant positive effects of parental language input.

For children who are DHH, the CELF-5/CELF Preschool-2, an assessment of children's ability to comprehend declarative sentences of increasing length and linguistic complexity, was the only receptive language outcome measure for which the association with parental sensitivity was significantly mediated by child inhibitory control (NIH Flanker) scores. The Following Directions subtest of the CELF-5/CELF Preschool-2 used in this study assessed the child's competency in syntactic and spatial language decoding while also making demands on active verbal working memory. Children who have hearing loss often differ from their counterparts with NH in aspects of language unevenly, with higher order language skills (comprehension, discourse) being the most difficult for them (Geers et al., 2003; Kronenberger & Pisoni, 2019; Nittrouer et al., 2018). The higher order language component of the CELF-5/CELF Preschool-2 Following Directions subtest may have been more sensitive to the indirect effect of inhibitory control in children who are DHH because of the greater demands on slow effortful language processing in these children. Recent evidence has demonstrated that higher order language skills in children who are DHH may be weaker than in children with NH because of delays in fast automatic language processing and increased demands on slow effortful information processing using EF (Kronenberger & Pisoni, 2019). An alternative hypothesis for these results would be that the CELF-5/CELF Preschool-2 was the most difficult language measure for both groups of children and was assessing an area of language under active development. Such skills that are being actively acquired are hypothesized in the attachment literature to be in the ephemeral “zone of proximal development” (Vygotsky, 1978) and, therefore, most sensitive to parental behaviors and intervention for the scaffolding of those skills.

Whereas parental sensitivity was the focus of this study, other components of family environment, parental interaction, and parental education have also been found to contribute to language outcomes in children with NH or who are DHH. These other components of the family likely interact with parental sensitivity and may provide additional developmental mechanisms by which parental sensitivity contributes to language and neurocognitive outcomes. The importance of early parental language input on children's language development has been well known from landmark research by Hart and Risley (1995). More recently, the 30 Million Words project displayed unequivocally that the amount of parental language input had a strong positive association with the language of children with NH (Suskind, 2015). These results suggested that parents who are more sensitive to their child's linguistic skills likely use more words overall in daily interactions and in more ways that are appropriately challenging and stimulating for their children, contributing to the wider, more varied, and richer child language output of those children. Maternal sensitivity and maternal linguistic stimulation both have been found to affect language acquisition and growth in children who are DHH, specifically through noun learning (Quittner et al., 2016). Higher level linguistic strategies and types of words used by the parent also predicted growth in the language of children who are DHH over time (Cruz et al., 2013). Positive relations between maternal sensitivity and linguistic stimulation have been reported in populations of children with NH or who are DHH (Roberts & Hampton, 2018; Vallotton et al., 2017), likely because parents who are more sensitive seek out and display different ways to scaffold and challenge their children verbally more often, and vice versa.

Parental education level has been associated with parental sensitivity in both children who are DHH and with NH (Newton et al., 2014; Pressman et al., 1999). Whether parental education is a direct antecedent to parental sensitivity is not resolved in the literature, but interventions for parents of children who are DHH regarding their language use and sensitivity have had preliminary effectiveness and utility (Lam-Cassettari et al., 2015). Because parental sensitivity is potentially malleable and can be addressed with early intervention in a way that parental education cannot, we focused on parental sensitivity and statistically controlled for small differences in parental education (the parents of the children with NH had a bachelor's degree on average, whereas the parents of the children who are DHH had an associate's degree/some college on average). Additionally, recent research has suggested that a mechanism through which parental education might affect child outcomes is through increasing time investment of parents with their children, emphasizing that interventions targeting parental behavior through intervention is likely a better modifier of the relation of parental education to child outcomes (Del Boca et al., 2016; Del Bono et al., 2016). Although the effect of parental education was controlled for in mediation analyses, it would be ideal to have the samples matched on parental education. The difficulty of balancing parental education levels by hearing group through recruitment is compounded by the underlying demographic distributions: The prevalence of children who are DHH increases with decreasing household income, a common proxy for parental education because the two are highly correlated with each other (Liberatos et al., 1988; National Center for Health Statistics, 1994; Neuhauser, 2018). Other studies examining parental sensitivity in children who are DHH have encountered the same issue and controlled for either parental education or household income in analyses (Pressman et al., 1999; Quittner et al., 2013).

In terms of the influence of the larger family environment on language development, better child language outcomes were found to be associated with the presence of learning materials in a home that is clean, bright, and minimally cluttered and where there are low levels of conflict among family members (Holt et al., 2020). Parents who display more sensitive behaviors may prioritize and take advantage of engagement opportunities with their children. Ultimately, the construct of parental sensitivity likely overlaps with other characteristics and behaviors, and this study extends the knowledge and understanding of the potential underlying mechanisms through which parents can affect their child's language.

Because this investigation used a cross-sectional design, causal mechanisms cannot be conclusively determined from these data. Rather, the results demonstrate consistency with a causal model, but other models may account for study findings. For example, the association between language and inhibitory control in children who are DHH is likely bidirectional. Nevertheless, bootstrap confidence interval mediation has been supported for use in cross-sectional designs to demonstrate consistency with an a priori theoretical model (Hayes, 2018).

An additional potential limitation is that our sample size of 62 children with NH and 64 children who are DHH may not have yielded sufficient power to detect small effect sizes, particularly for mediator models (Kenny & Judd, 2014). For any indirect effect smaller in standardized βi coefficients than 0.250 (of which our largest detected standardized βi coefficient was 0.099), more than 100 participants are suggested for each model for effect detection (Kenny & Judd, 2014). As such, the significant indirect effect and trends toward significant effects (as shown by variable correlations) that were found in children who are DHH are consistent with effect sizes in the medium range, accounting for a nontrivial amount of the variance in language outcomes. Nevertheless, research with larger sample sizes is necessary to test small-to-medium effect sizes in associations between parental sensitivity and child inhibitory control and language.

Conclusions

The effects of parents and their behaviors on child development are widely acknowledged as fundamental components contributing to later child success (Fay-Stammbach et al., 2014; Kochanska & Aksan, 1995; Newton et al., 2014; Tamis-LeMonda et al., 2001). In this study, parental sensitivity was found to be significantly related to children's spoken language and inhibitory control skills in children who are DHH, but not children with NH of the same age. A measure of receptive sentence comprehension provided evidence for an indirect effect of parental sensitivity through child inhibitory control in children who are DHH, but not children with NH. The relation of parental sensitivity to inhibitory control was significant in children who use HAs, but not CIs, when the group of children who are DHH were subdivided, suggesting that this potential developmental pathway may differ by characteristics of the audiological experience of the child. However, more participants with each type of device are required to understand any potential differences between these subgroups of children with hearing loss. By demonstrating the differences in contributors to various aspects of school-age child language in populations of children with NH or who are DHH, this study provides the foundation for further investigation into the differing needs of children who use HAs and CIs in terms of parental influence on their language and neurocognitive development. Preliminary research investigating the feasibility of addressing parental sensitivity in children who are DHH using video feedback intervention may have promise for clinical application of these findings (Lam-Cassettari et al., 2015). Future work is recommended to further develop interventions to improve parental sensitivity in children who are DHH and thus at risk for language delays and to evaluate the impact of intervening to support parental sensitivity (and other relevant family contributors) on language outcomes.

Appendix

Behavioral Coding Interrater Reliability

Table A1.

Interrater reliability for training videos using intraclass correlation values.

Scale	ICC value	Scale	ICC value
Sensitivity/responsivity	.754	Underactivity	−.169
Supportive presence	.750	Overactivity/hyperactivity	.974
Intrusiveness/overcontrol	.923	Negativity/hostility toward the mother	.869
Respect for child's autonomy	.828	Positive engagement with mother	.651
Detachment	.626	Affection toward mother	.748
Stimulation of cognitive development	.807	Persistence/sustained attention	.937
Positive regard	.791	Enthusiasm	.854
Negative regard/hostility	.744	Joint attention	.793
Flatness	.888	Affective mutuality	.779
Language amount	.846	Mutual enjoyment	.863
Positive mood	.823	Reciprocal interaction	.336
Negative mood	.914

Note. Thirteen training videos from a previous study were coded by two coders and assessed for interrater reliability. ICC = two-way random intraclass correlation value between two coders.

Table A2.

Interrater reliability for test videos using intraclass correlation values.

Scale	ICC value	Scale	ICC value
Sensitivity/responsivity	.725	Underactivity	−.092
Supportive presence	.846	Overactivity/hyperactivity	.825
Intrusiveness/overcontrol	.785	Negativity/hostility toward the mother	.638
Respect for child's autonomy	.558	Positive engagement with mother	.785
Detachment	.841	Affection toward mother	.678
Stimulation of cognitive development	.881	Persistence/sustained attention	.619
Positive regard	.744	Enthusiasm	.743
Negative regard/hostility	.459	Joint attention	.795
Flatness	.758	Affective mutuality	.748
Language amount	.728	Mutual enjoyment	.654
Positive mood	.731	Reciprocal interaction	.746
Negative mood	.155

Note. Twenty-five percent of the 126 total videos were randomly selected and coded by both coders. These 32 videos were assessed for interrater reliability using intraclass correlation values. ICC = two-way random intraclass correlation value between two coders.

Funding Statement

This research was funded by NIH-NIDCD R01DC014956 (to R. F. Holt & D. B. Pisoni, MPIs).