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Abstract: For children who are born deaf, lipreading (speechreading) is an important source of access to spoken language. We used eye tracking to investigate the strategies used by deaf (n = 33) and hearing 5–8‐year‐olds (n = 59) during a sentence speechreading task. The proportion of time spent looking at the mouth during speech correlated positively with speechreading accuracy. In addition, all children showed a tendency to watch the mouth during speech and watch the eyes when the model was not speaking. The extent to which the children used this communicative pattern, which we refer to as social‐tuning, positively predicted their speechreading performance, with the deaf children showing a stronger relationship than the hearing children. These data suggest that better speechreading skills are seen in those children, both deaf and hearing, who are able to guide their visual attention to the appropriate part of the image and in those who have a good understanding of conversational turn‐taking. [ABSTRACT FROM AUTHOR]

For children who are born deaf, lipreading (speechreading) is an important source of access to spoken language. We used eye tracking to investigate the strategies used by deaf (n = 33) and hearing 5-8-year-olds (n = 59) during a sentence speechreading task. The proportion of time spent looking at the mouth during speech correlated positively with speechreading accuracy. In addition, all children showed a tendency to watch the mouth during speech and watch the eyes when the model was not speaking. The extent to which the children used this communicative pattern, which we refer to as socialtuning, positively predicted their speechreading performance, with the deaf children showing a stronger relationship than the hearing children. These data suggest that better speechreading skills are seen in those children, both deaf and hearing, who are able to guide their visual attention to the appropriate part of the image and in those who have a good understanding of conversational turn-taking. [ABSTRACT FROM AUTHOR]

A Delphi consensus methodology was used to adapt the Autism Diagnostic Interview–Revised for the assessment of deaf children with suspected autism spectrum disorder. Each Autism Diagnostic Interview–Revised item was considered by a panel of nine international experts in terms of relevance and acceptability. Modifications were proposed and agreed by the expert panel for 45% of items. The pre-specified criterion for agreement between experts was set at 80% for each item. A first validation of the revised version, adapted for deaf children (Autism Diagnostic Interview–Revised Deaf Adaptation), was undertaken with a UK sample of 78 parents/carers of deaf children with autism spectrum disorder and 126 parents/carers with deaf children without autism spectrum disorder. When compared to National Institute for Health and Care Excellence guideline standard clinical assessments, the Autism Diagnostic Interview–Revised Deaf Adaptation diagnostic algorithm cut-off/threshold scores achieved a sensitivity of 89% (79%–96%) and specificity of 81% (70%–89%) for autism spectrum disorder. The alpha coefficients for each algorithm symptom domain ranged from 0.80 to 0.91, suggesting that the items had high internal consistency. Our findings indicate that the Autism Diagnostic Interview–Revised Deaf Adaptation is likely to be a useful measure for the assessment of deaf children with suspected autism spectrum disorder, although further research is needed. Autism assessment processes need to improve for deaf children as they are currently being diagnosed later than their hearing counterparts and misdiagnosis can occur. We took one of the most commonly used parent developmental interviews for autism spectrum disorder the Autism Diagnostic Interview–Revised and adapted it using international expert advice. Modifications were proposed and agreed by the expert panel for 45% of items; the remaining 55% of items were unchanged. We then tested the revised version, adapted for deaf children (Autism Diagnostic Interview–Revised Deaf Adaptation), in a UK sample of 78 parents/carers of deaf children with autism spectrum disorder and 126 parents/carers with deaf children without autism spectrum disorder. When compared to National Institute for Health and Care Excellence guideline standard clinical assessments, the Autism Diagnostic Interview–Revised Deaf Adaptation diagnostic algorithm threshold scores could identify those deaf children with a definite diagnosis (true autism spectrum disorder positives) well (sensitivity of 89% (79%–96%)) and those deaf children who did not have autism spectrum disorder (true autism spectrum disorder negatives) well (specificity of 81% (70%–89%)). Our findings indicate that the Autism Diagnostic Interview–Revised Deaf Adaptation is likely to prove a useful measure for the assessment of deaf children with suspected autism spectrum disorder and that further research would be helpful. [ABSTRACT FROM AUTHOR]

A Delphi consensus methodology was used to adapt a screening tool, the Social Responsiveness Scale– 2 (SRS-2), for use with deaf children including those whose preferred communication method is sign language. Using this approach; 27 international experts (The Delphi International Expert Panel), on the topic of autism spectrum disorder (ASD) in deaf people, contributed to the review of item content. A criterion for agreement was set at 80% of experts on each item (with 75% acceptable in the final fourth round). The agreed modifications are discussed. The modified SRS-2 research adaptation for deaf people (referred to here as the "SRS-2 Deaf adaptation") was then translated into British Sign Language using a robust translation methodology and validated in England in a sample of 198 deaf children, 76 with Autism Spectrum Disorders (ASD) and 122 without ASD. The SRS-2 Deaf adaptation was compared blind to a NICE (National Institute for Health and Care Excellence) guideline standard clinical assessment. The area under the Receiver Operating (ROC) curve was 0.811 (95% CI: 0.753, 0.869), with an optimal cut-off value of 73, which gave a sensitivity of 82% and a specificity of 67%. The Cronbach Alpha coefficient was 0.968 suggesting high internal consistency. The Intraclass Correlation Coefficient was 0.897, supporting test-retest reliability. This performance is equivalent to similar instruments used for screening ASD in the hearing population. [ABSTRACT FROM AUTHOR]

Purpose: Speechreading (lipreading) is a correlate of reading ability in both deaf and hearing children. We investigated whether the relationship between speechreading and singleword reading is mediated by phonological awareness in deaf and hearing children. Method: In two separate studies, 66 deaf children and 138 hearing children, aged 5-8 years old, were assessed on measures of speechreading, phonological awareness, and single-word reading. We assessed the concurrent relationships between latent variables measuring speechreading, phonological awareness, and single-word reading. Results: In both deaf and hearing children, there was a strong relationship between speechreading and singleword reading, which was fully mediated by phonological awareness. Conclusions: These results are consistent with ideas from previous studies that visual speech information contributes to the development of phonological representations in both deaf and hearing children, which, in turn, support learning to read. Future longitudinal and training studies are required to establish whether these relationships reflect causal effects. [ABSTRACT FROM AUTHOR]

Purpose: We developed and evaluated in a randomized controlled trial a computerized speechreading training program to determine (a) whether it is possible to train speechreading in deaf children and (b) whether speechreading training results in improvements in phonological and reading skills. Previous studies indicate a relationship between speechreading and reading skill and further suggest this relationship may be mediated by improved phonological representations. This is important since many deaf children find learning to read to be very challenging. Method: Sixty-six deaf 5- to 7-year-olds were randomized into speechreading and maths training arms. Each training program was composed of a 10-min sessions a day, 4 days a week for 12 weeks. Children were assessed on a battery of language and literacy measures before training, immediately after training, and 3 months and 11 months after training. Results: We found no significant benefits for participants who completed the speechreading training, compared to those who completed the maths training, on the speechreading primary outcome measure. However, significantly greater gains were observed in the speechreading training group on one of the secondary measures of speechreading. There was also some evidence of beneficial effects of the speechreading training on phonological representations; however, these effects were weaker. No benefits were seen to word reading. Conclusions: Speechreading skill is trainable in deaf children. However, to support early reading, training may need to be longer or embedded in a broader literacy program. Nevertheless, a training tool that can improve speechreading is likely to be of great interest to professionals working with deaf children. [ABSTRACT FROM AUTHOR]