Publications by authors named "Amy Nicholson"

Purpose: Developmental assessment is part of a comprehensive autism evaluation. During in-person evaluations, developmental assessment is completed via direct testing by an examiner. In telehealth evaluations, developmental assessment relies on caregiver-report instruments.

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This Letter presents the first lattice QCD computation of the coupled channel πΣ-K[over ¯]N scattering amplitudes at energies near 1405 MeV. These amplitudes contain the resonance Λ(1405) with strangeness S=-1 and isospin, spin, and parity quantum numbers I(J^{P})=0(1/2^{-}). However, whether there is a single resonance or two nearby resonance poles in this region is controversial theoretically and experimentally.

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Purpose: Telemedicine approaches to autism (ASD) assessment have become increasingly common, yet few validated tools exist for this purpose. This study presents results from a clinical trial investigating two approaches to tele-assessment for ASD in toddlers.

Methods: 144 children (29% female) between 17 and 36 months of age (mean = 2.

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This randomized controlled trial (NCT03889821) examined Mindfulness Based Stress Reduction (MBSR) in conjunction with the Parent-implemented Early Start Denver Model (P-ESDM). A previous report described improved metrics of parental distress (Weitlauf et al. in Pediatrics 145(Supplement 1):S81-S92, 2020).

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The COVID-19 pandemic has increased the use of telemedicine as an avenue to address the need for diagnostic clarification in young children at risk for autism spectrum disorder (ASD). Although preliminary research has supported the use of telemedicine for identifying ASD in toddlers, little is known about the experiences of practitioners attempting direct-to-home tele-assessment. We surveyed diagnostic providers regarding changes in practice behavior in the initial months of the COVID-19 pandemic and their perceptions of ASD tele-assessment.

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Barriers to identifying autism spectrum disorder (ASD) in young children in a timely manner have led to calls for novel screening and assessment strategies. Combining computational methods with clinical expertise presents an opportunity for identifying patterns within large clinical datasets that can inform new assessment paradigms. The present study describes an analytic approach used to identify key features predictive of ASD in young children, drawn from large amounts of data from comprehensive diagnostic evaluations.

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The COVID-19 pandemic has caused unprecedented disruptions to healthcare, including direct impacts on service delivery related to autism spectrum disorder (ASD). Caregiver-mediated tele-assessment offers an opportunity to continue services while adhering to social distancing guidelines. The present study describes a model of tele-assessment for ASD in young children, implemented in direct response to disruptions in care caused by the COVID-19 pandemic.

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Telemedicine tools have potential for increasing access to diagnostic services for children with autism spectrum disorder (ASD). Past work has utilized tele-assessment procedures in which remote psychologists observe administration of interactive screening instruments by trained, on-site providers. Although promising, this approach relies on two clinicians, limiting its efficiency and scalability.

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Background And Objectives: Systems of care emphasize parent-delivered intervention for children with autism spectrum disorder (ASD). Meanwhile, multiple studies document psychological distress within these parents. This pilot longitudinal randomized controlled trial compared the parent-implemented Early Start Denver Model (P-ESDM) to P-ESDM plus mindfulness-based stress reduction (MBSR) for parents.

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As prevalence of autism spectrum disorder continues to increase, so too does the need for timely, accessible diagnostic consultation. The present work extends from a previous study which provided preliminary evidence for the feasibility of expert clinicians to utilize telemedicine to triage autism spectrum disorder risk in young children. However, it did not examine whether a telediagnostic model had a demonstrable impact on tertiary care center referrals and usage.

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Increasing access to diagnostic services is crucial for identifying ASD in young children. We therefore evaluated a telemedicine assessment procedure. First, we compared telediagnostic accuracy to blinded gold-standard evaluations (n = 20).

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The ground state energies of universal N-body clusters tied to Efimov trimers, for N even, are shown to be encapsulated in the statistical distribution of two particles interacting with a background auxiliary field at large Euclidean time when the interaction is tuned to the unitary point. Numerical evidence that this distribution is log normal is presented, allowing one to predict the ground state energies of the N-body system.

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We show how sign problems in simulations of many-body systems can manifest themselves in the form of heavy-tailed correlator distributions, similar to what is seen in electron propagation through disordered media. We propose an alternative statistical approach for extracting ground state energies in such systems, illustrating the method with a toy model and with lattice data for unitary fermions.

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Autism spectrum disorder (ASD) is considered among the most heritable of all neurodevelopmental and psychiatric disorders, but identification of etiologically significant genetic markers and risk variants has been hampered by a lack of sufficiently large samples. Rapid phenotyping procedures, where self-report measures are used instead of extensive clinical assessment, have been proposed as methods for amassing large genetic databases due to their hypothesized time-efficiency and affordability. We assessed the diagnostic accuracy of potential rapid phenotyping procedures using the Social Communication Questionnaire and the Social Responsiveness Scale in a sample of 333 children who also received extensive phenotypic assessments.

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