RESUMEN
This study examined the psychometric characteristics of the Cambridge-Mindreading Face-Voice Battery for Children (CAM-C) for a sample of 333 children, ages 6-12 years with ASD (with no intellectual disability). Internal consistency was very good for the Total score (0.81 for both Faces and Voices) and respectable for the Complex emotions score (0.72 for Faces and 0.74 for Voices); however, internal consistency was lower for Simple emotions (0.65 for Faces and 0.61 for Voices). Test-retest reliability at 18 and 36 weeks was very good for the faces and voices total (0.76-0.81) and good for simple and complex faces and voices (0.53-0.75). Significant correlations were found between CAM-C Faces and scores on another measure of face-emotion recognition (Diagnostic Analysis of Nonverbal Accuracy-Second Edition), and between Faces and Voices scores and child age, IQ (except perceptual IQ and Simple Voice emotions), and language ability. Parent-reported ASD symptom severity and the Emotion Recognition scale on the SRS-2 were not related to CAM-C scores. Suggestions for future studies and further development of the CAM-C are provided. LAY SUMMARY: Facial and vocal emotion recognition are important for social interaction and have been identified as a challenge for individuals with autism spectrum disorder. Emotion recognition is an area frequently targeted by interventions. This study evaluated a measure of emotion recognition (the CAM-C) for its consistency and validity in a large sample of children with autism. The study found the CAM-C showed many strengths needed to accurately measure the change in emotion recognition during intervention.
Asunto(s)
Trastorno del Espectro Autista , Reconocimiento Facial , Voz , Niño , Emociones , Expresión Facial , Humanos , Psicometría , Reproducibilidad de los ResultadosRESUMEN
There's no denying that the electronic health record is on its way. By taking the following five well-planned steps, healthcare CFOs and CIOs can help make electronic record implementation in their hospitals as smooth as possible: Define "electronic health record" across the entire organization, Set appropriate expectations, Choose the technology carefully, Accept and promote process changes, Carefully plan the transition from paper-based to electronic records.