The interaction of fine motor, gesture, and structural language skills: The case of autism spectrum disorder

Does Gestural Communication Influence Later Spoken Language Ability in Minimally Verbal Autistic Children?

PURPOSE

The current study examined the predictive role of gestures and gesture-speech combinations on later spoken language outcomes in minimally verbal (MV) autistic children enrolled in a blended naturalistic developmental/behavioral intervention (Joint Attention, Symbolic Play, Engagement, and Regulation [JASPER] + Enhanced Milieu Teaching [EMT]).

METHOD

Participants were 50 MV autistic children (40 boys), ages 54-105 months (M = 75.54, SD = 16.45). MV was defined as producing fewer than 20 spontaneous, unique, and socially communicative words. Autism symptom severity (Autism Diagnostic Observation Schedule-Second Edition) and nonverbal cognitive skills (Leiter-R Brief IQ) were assessed at entry. A natural language sample (NLS), a 20-min examiner-child interaction with specified toys, was collected at entry (Week 1) and exit (Week 18) from JASPER + EMT intervention. The NLS was coded for gestures (deictic, conventional, and representational) and gesture-speech combinations (reinforcing, disambiguating, supplementary, other) at entry and spoken language outcomes: speech quantity (rate of speech utterances) and speech quality (number of different words [NDW] and mean length of utterance in words [MLUw]) at exit using European Distributed Corpora Project Linguistic Annotator and Systematic Analysis of Language Transcripts.

RESULTS

Controlling for nonverbal IQ and autism symptom severity at entry, rate of gesture-speech combinations (but not gestures alone) at entry was a significant predictor of rate of speech utterances and MLUw at exit. The rate of supplementary gesture-speech combinations, in particular, significantly predicted rate of speech utterances and NDW at exit.

CONCLUSION

These findings highlight the critical importance of gestural communication, particularly gesture-speech (supplementary) combinations in supporting spoken language development in MV autistic children.

The relationship between executive function and the association of motor coordination difficulties and social communication deficits in autistic children

Background

Motor coordination difficulties could contribute to social communication deficits in autistic children. However, the exploration of the mechanism implicated in these claims has been limited by the lack of potential confounders such as executive function (EF).

Methods

We investigated the role that EF plays in the relationship between motor coordination and social communication in a school-aged autistic population via a structural model in a statistically robust manner. The results of questionnaires, including the Developmental Coordination Disorder questionnaire, the Behavior Rating Inventory of Executive Function, and the Social Responsiveness Scale, were collected to measure motor coordination, social communication deficits, and EF.

Results

A total of 182 autistic children (7.61±1.31 years, 87.9% boys) were included in the final analysis. In the model with EF as a mediator, the total effect (β=-0.599, P<0.001) and the direct effect (β=-0.331, P =0.003) of motor coordination function on social communication were both significant among autistic children without intellectual disability (ID), as were indirect effects through EF (β=-0.268, P<0.001).

Conclusion

EF partially mediates the motor coordination and social communication correlation among autistic children. We suggest that motor coordination should be included in the routine evaluation of autistic surveillance and rehabilitation procedures.

[A review of studies on visual behavior analysis aided diagnosis of autism spectrum disorders]

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and repetitive behaviors. With the rapid development of computer vision, visual behavior analysis aided diagnosis of ASD has got more and more attention. This paper reviews the research on visual behavior analysis aided diagnosis of ASD. First, the core symptoms and clinical diagnostic criteria of ASD are introduced briefly. Secondly, according to clinical diagnostic criteria, the interaction scenes are classified and introduced. Then, the existing relevant datasets are discussed. Finally, we analyze and compare the advantages and disadvantages of visual behavior analysis aided diagnosis methods for ASD in different interactive scenarios. The challenges in this research field are summarized and the prospects of related research are presented to promote the clinical application of visual behavior analysis in ASD diagnosis.

INC-Hg: An Intelligent Collaborative Haptic-Gripper Virtual Reality System

Collaborative Virtual Environments (CVE) have shown potential to be an effective social skill training platform for children with Autism Spectrum Disorders (ASD) to learn and practice collaborative and communication skills through peer interactions. However, most existing CVE systems require that appropriately matched partners be available at the same time to promote interaction, which limits their applicability to some community settings due to scheduling constraints. A second shortcoming of these more naturalistic peer-based designs is the intensive resources required to manually code the unrestricted conversations that occurred during the peer-based interactions. To preserve the benefits of CVE-based platforms and mitigate some of the resource limitations related to peer availability, we developed an Intelligent Collaborative Haptic-Gripper System (INC-Hg). This system provides an intelligent agent partner who can understand, communicate, and haptically interact with the user, without requiring the presence of another human peer. The INC-Hg operates in real time and thus is able to perform collaborative training tasks at any time and at the user's pace. INC-Hg can also record the real-time data regarding spoken language and task performance, thereby greatly reducing the resource burden of communication and interaction performance analysis. A preliminary usability study with 10 participants with ASD (ages 8–12 years) indicated that the system could classify the participant's utterances into five classes with an accuracy of 70.34%, which suggested the potential of INC-Hg to automatically recognize and analyze conversational content. The results also indicated high accuracies of the agent to initiate a conversation (97.56%) and respond to the participants (86.52%), suggesting the capability of the agent to conduct proper conversations with the participants. Compared to the results of human-to-human collaborative tasks, the human-to-agent mode achieved higher average collaborative operation ratio (61% compared to 40%) and comparable average frequencies for Initiations and Responses among the participants with ASD. These results offer preliminary support as well as areas of improvement regarding the agent's ability to respond to participants, work with participants to complete tasks, engage in back-and-forth conversations, and support the potential of the agent to be a useful partner for individuals with ASD completing CVE tasks.

Motor skills predict adaptive behavior in autistic children and adolescents

It is well-documented that intelligence quotient (IQ) is a poor predictor of adaptive behavior scores in autism, with autistic children having lower adaptive behavior scores than would be predicted based on their IQ scores. Differences in motor skills may explain the variability in their adaptive behavior scores. The current study examined how motor skills might explain autistic individuals' low adaptive behavior scores and which individual components of IQ (i.e., verbal comprehension and perceptual reasoning) and motor skills (i.e., manual dexterity, aiming and catching, and balance) may drive this effect. We examined the associations between IQ, motor skills, calibrated severity, and adaptive behavior scores in 45 autistic children and adolescents. Using a t-test, we found a significant difference (p <0.001) between full-scale IQ and adaptive behavior scores, indicating that our participants' adaptive behavior scores were lower than would be expected given their full-scale IQ. Using a linear regression, we investigated whether motor skills predicted adaptive behavior in autistic children and adolescents and found that motor skills scores were associated with adaptive behavior scores (p = 0.022). To further investigate these associations, we used another linear regression to examine how individual components of IQ and motor skills predicted adaptive behavior scores in autistic children and adolescents. Our results indicated that manual dexterity scores were associated with adaptive behavior scores (p = 0.036). These findings clearly illustrate the need for further understanding of autistic individuals' difficulties with adaptive behavior and the potential role of motor skill difficulties that may underlie these difficulties. LAY SUMMARY: Autistic children have lower adaptive behavior scores (e.g., daily living skills, social skills, communication) than intelligence scores (e.g., verbal and perceptual skills) along with difficulties with motor skills. Motor skills may explain the gap between adaptive behavior and intelligence. We found motor skills were associated with adaptive behavior in autistic children and adolescents. In particular, hand coordination was associated with adaptive behavior. We need to better understand how autistic individuals' motor skills impact their adaptive behavior to provide effective supports.