RESUMO
Use of telehealth assessments for toddlers at increased likelihood of autism spectrum disorder (ASD) began prior to the global COVID-19 pandemic; however, the value of telehealth assessments as an alternative to in-person assessment (IPA) became clearer during the pandemic. The Naturalistic Observation Diagnosis Assessment (NODA™), previously demonstrated as a valid and reliable tool to evaluate asynchronous behaviors for early diagnosis, was enhanced to add synchronous collection of behaviors to assist clinicians in making a differential diagnosis of ASD. This study was conducted to validate the information gathered through NODA-Enhanced (NODA-E™) as compared to a gold standard IPA. Forty-nine toddlers aged 16.0-32.1 months of age, recruited through community pediatric offices and a tertiary ASD clinic, participated in both NODA-E and IPA assessments. There was high agreement between the two assessment protocols for overall diagnosis (46 of 49 cases; 93.6%; κ = .878), specific diagnostic criteria for social communication and social interaction (SCI; range 95.9-98%; κ = .918-.959), and for two of four criteria specified for restricted and repetitive behaviors (RRB; range 87.8-98%; κ = .755 and .959). There was lower agreement for two subcategories of RRBs (range 65.3-67.3%; κ = .306 and .347). NODA-E is a tool that can assist clinicians in making reliable and valid early ASD diagnoses using both asynchronous and synchronous information gathered via telehealth and offers an additional tool within a clinician's assessment toolbox.
RESUMO
Research indicates that a substantial amount of time elapses between parents' first concerns about their child's development and a formal diagnosis of autism spectrum disorder (ASD). Telehealth presents an opportunity to expedite the diagnostic process. This project compared a novel telehealth diagnostic approach that utilizes clinically guided in-home video recordings to the gold standard in-person diagnostic assessment. Participants included 40 families seeking an ASD evaluation for their child and 11 families of typically developing children. Children were between the ages of 18 months and 6 years 11 months; mean adaptive behavior composite = 75.47 (SD = 15.94). All parent participants spoke English fluently. Families completed the Naturalistic Observation Diagnostic Assessment (NODA) for ASD, which was compared to an in-person assessment (IPA). Agreement between the 2 methods, as well as sensitivity, specificity, and interrater reliability, were calculated for the full sample and the subsample of families seeking an ASD evaluation. Diagnostic agreement between NODA and the IPA was 88.2% (κ = 0.75) in the full sample and 85% (κ = 0.58) in the subsample. Sensitivity was 84.9% in both, whereas specificity was 94.4% in the full sample and 85.7% in the subsample. Kappa coefficients for interrater reliability indicated 85% to 90% accuracy between raters. NODA utilizes telehealth technology for families to share information with professionals and provides a method to inform clinical judgment for a diagnosis of ASD. Due to the high level of agreement with the IPA in this sample, NODA has potential to improve the efficiency of the diagnostic process for ASD. (PsycINFO Database Record
Assuntos
Transtorno do Espectro Autista/diagnóstico , Comportamento Infantil , Telemedicina , Gravação em Vídeo , Estudos de Casos e Controles , Criança , Desenvolvimento Infantil , Pré-Escolar , Feminino , Humanos , Lactente , Masculino , Pais , Reprodutibilidade dos Testes , Sensibilidade e EspecificidadeRESUMO
With the prevalence of diagnosed autism on the rise, increased efforts are needed to support surveillance, research, and case management. Challenges to collect, analyze and share typical and unique patient information and observations are magnified by expanding provider caseloads, delays in treatment and patient office visits, and lack of sharable data. This paper outlines recommended principles and approaches for utilizing state-of-the-art information systems technology and population-based registries to facilitate collection, analysis, and reporting of autism patient data. Such a platform will increase treatment options and registry information to facilitate diagnosis, treatment and research of this disorder.
Assuntos
Transtorno Autístico , Informática Médica , Humanos , Disseminação de Informação , Sistemas de Informação , Sistema de RegistrosRESUMO
BACKGROUND: Observing behavior in the natural environment is valuable to obtain an accurate and comprehensive assessment of a child's behavior, but in practice it is limited to in-clinic observation. Research shows significant time lag between when parents first become concerned and when the child is finally diagnosed with autism. This lag can delay early interventions that have been shown to improve developmental outcomes. OBJECTIVE: To develop and evaluate the design of an asynchronous system that allows parents to easily collect clinically valid in-home videos of their child's behavior and supports diagnosticians in completing diagnostic assessment of autism. METHODS: First, interviews were conducted with 11 clinicians and 6 families to solicit feedback from stakeholders about the system concept. Next, the system was iteratively designed, informed by experiences of families using it in a controlled home-like experimental setting and a participatory design process involving domain experts. Finally, in-field evaluation of the system design was conducted with 5 families of children (4 with previous autism diagnosis and 1 child typically developing) and 3 diagnosticians. For each family, 2 diagnosticians, blind to the child's previous diagnostic status, independently completed an autism diagnosis via our system. We compared the outcome of the assessment between the 2 diagnosticians, and between each diagnostician and the child's previous diagnostic status. RESULTS: The system that resulted through the iterative design process includes (1) NODA smartCapture, a mobile phone-based application for parents to record prescribed video evidence at home; and (2) NODA Connect, a Web portal for diagnosticians to direct in-home video collection, access developmental history, and conduct an assessment by linking evidence of behaviors tagged in the videos to the Diagnostic and Statistical Manual of Mental Disorders criteria. Applying clinical judgment, the diagnostician concludes a diagnostic outcome. During field evaluation, without prior training, parents easily (average rating of 4 on a 5-point scale) used the system to record video evidence. Across all in-home video evidence recorded during field evaluation, 96% (26/27) were judged as clinically useful, for performing an autism diagnosis. For 4 children (3 with autism and 1 typically developing), both diagnosticians independently arrived at the correct diagnostic status (autism versus typical). Overall, in 91% of assessments (10/11) via NODA Connect, diagnosticians confidently (average rating 4.5 on a 5-point scale) concluded a diagnostic outcome that matched with the child's previous diagnostic status. CONCLUSIONS: The in-field evaluation demonstrated that the system's design enabled parents to easily record clinically valid evidence of their child's behavior, and diagnosticians to complete a diagnostic assessment. These results shed light on the potential for appropriately designed telehealth technology to support clinical assessments using in-home video captured by families. This assessment model can be readily generalized to other conditions where direct observation of behavior plays a central role in the assessment process.
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Families, clinicians and researchers involved with varying neurological disorders face amazing challenges to understand, treat, and assist the people they are serving. Autism brings unique challenges and serves as an important model for the application of important concepts in information technology and telemedicine. The rising incidence of autism with limited professional resources has led to more consideration for using information technology and related specialties to link families and professionals, and to implement strategies which implement information technology to improve the outcomes for individuals with autism and their families. These are reviewed in context of the unique health, education, and the research issues facing those dealing with autism.