Treatment of Pediatric Functional Neurological Symptom Disorder: A Review of the State of the Literature.

Functional Neurological Symptom Disorder (FNSD), or experiencing neurological symptoms incompatible with either a neurological condition or a medical condition, is a common condition presenting in children and adolescents. It is associated with impairment in quality of life for patients and their families and represents a significant burden to the healthcare system. There is currently limited research available regarding effective treatment of pediatric FNSD. Currently, only one RCT exists studying effective treatment of FNSD in children and adolescents, and it is limited to one sub-type of FNSD and only examined cognitive behavioral therapy compared to supportive therapy. Despite this, almost all published research supports good prognosis for pediatric FNSD with all studies reporting improvement either in FNSD symptoms or in the quality of life and functioning of patients with FNSD. The most support was found for the use of cognitive behavioral therapy either as a stand-alone treatment or in the context of interdisciplinary treatment. Future research should focus on increasing the rigor of research, including expanding RCTs to include additional sub-types of FNSD and comparing across various treatment modalities.

How effective is LENA in detecting speech vocalizations and language produced by children and adolescents with ASD in different contexts?

The LENA system was designed and validated to provide information about the language environment in children 0 to 4 years of age and its use has been expanded to populations with a number of communication profiles. Its utility in children 5 years of age and older is not yet known. The present study used acoustic data from two samples of children with autism spectrum disorders (ASD) to evaluate the reliability of LENA automated analyses for detecting speech utterances in older, school age children, and adolescents with ASD, in clinic and home environments. Participants between 5 and 18 years old who were minimally verbal (study 1) or had a range of verbal abilities (study 2) completed standardized assessments in the clinic (study 1 and 2) and in the home (study 2) while speech was recorded from a LENA device. We compared LENA segment labels with manual ground truth coding by human transcribers using two different methods. We found that the automated LENA algorithms were not successful (<50% reliable) in detecting vocalizations from older children and adolescents with ASD, and that the proportion of speaker misclassifications by the automated system increased significantly with the target-child's age. The findings in children and adolescents with ASD suggest possibly misleading results when expanding the use of LENA beyond the age ranges for which it was developed and highlight the need to develop novel automated methods that are more appropriate for older children. Autism Research 2019, 12: 628-635. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Current commercially available speech detection algorithms (LENA system) were previously validated in toddlers and children up to 48 months of age, and it is not known whether they are reliable in older children and adolescents. Our data suggest that LENA does not adequately capture speech in school age children and adolescents with autism and highlights the need to develop new automated methods for older children.

Statistical Learning is Associated with Autism Symptoms and Verbal Abilities in Young Children with Autism.

Statistical learning-extracting regularities in the environment-may underlie complex social behavior. 124 children, 56 with autism and 68 typically developing, ages 2-8 years, completed a novel visual statistical learning task on an iPad. Averaged together, children with autism demonstrated less learning on the task compared to typically developing children. However, multivariate classification analyses characterized individual behavior patterns, and demonstrated a subset of children with autism had similar learning patterns to typically developing children and that subset of children had less severe autism symptoms. Therefore, statistically averaging data resulted in missing critical heterogeneity. Variability in statistical learning may help to understand differences in autism symptoms across individuals and could be used to tailor and inform treatment decisions.

Smartphone measures of day-to-day behavior changes in children with autism.

Smartphones offer a flexible tool to collect data about mental health, but less is known about their effectiveness as a method to assess variability in children's problem behaviors. Caregivers of children with autism completed daily questions about irritability, anxiety and mood delivered via smartphones across 8-weeks. Smartphone questions were consistent with subscales on standard caregiver questionnaires. Data collection from 7 to 10 days at the beginning and 7 to 10 days at the end of the study were sufficient to capture similar amounts of variance as daily data across 8-weeks. Other significant findings included effects of caregiver socioeconomic status and placebo-like effects from participation even though the study included no specific treatment. Nevertheless, single questions via smartphones collected over relatively brief periods reliably represent subdomains in standardized behavioral questionnaires, thereby decreasing burden on caregivers.

Placebo-like response in absence of treatment in children with Autism.

Caregiver report is the most common measure of change in pediatric psychiatry. Yet, placebo response rates pose significant challenges to reliably detect a treatment response. The present study simulated an eight-week clinical trial protocol for Autism Spectrum Disorder (ASD) for the purpose of testing the feasibility and validity of several outcome measures. Twenty caregivers answered questions about their child's behavior on their smartphone each week and completed a battery of paper questionnaires during weeks one and eight. No treatment was administered. Caregivers reported a significant decrease in problem behaviors on the Aberrant Behavior Checklist (ABC) (29% decrease) and general ASD behaviors on the Social Responsiveness Scale (SRS) (7% decrease). There was also a trend of behavior improvement from smartphone questions but no significant changes in clinical ratings of core diagnostic features of ASD. Participation in a comprehensive protocol in the absence of a particular treatment significantly influenced how caregivers perceived the severity of their children's problem behaviors. These placebo-like effects represent substantial challenges for randomized controlled trials (RCTs) that use treatment as usual and have implications for future behavioral and pharmacological treatment trial designs. Autism Res 2017, 10: 1567-1572. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Increased Eye Contact During Conversation Compared to Play in Children With Autism.

Children with autism have atypical gaze behavior but it is unknown whether gaze differs during distinct types of reciprocal interactions. Typically developing children (N = 20) and children with autism (N = 20) (4-13 years) made similar amounts of eye contact with an examiner during a conversation. Surprisingly, there was minimal eye contact during interactive play in both groups. Gaze behavior was stable across 8 weeks in children with autism (N = 15). Lastly, gaze behavior during conversation but not play was associated with autism social affect severity scores (ADOS CSS SA) and the Social Responsiveness Scale (SRS-2). Together findings suggests that eye contact in typical and atypical development is influenced by subtle changes in context, which has implications for optimizing assessments of social communication skills.