Lead Lab Active Studies

• Testing the Impact of Early Screening on the Long-term Outcomes of Children with ASD (Project EARLY Follow-up Study)
Autism spectrum disorder (ASD) impacts almost 2% of children born today, yet very little is known regarding how to positively alter the outcomes of affected children. There is currently debate on whether universal early screening of ASD is linked to positive outcomes for children. What is needed to inform the debate is to examine the outcomes of a large cohort of children detected very early via universal screening at well-baby checks, and to compare them to children who did not participate in an early detection program. This study examines changes in symptoms, IQ, and self-help skills between toddlers and school aged children with autism who did and did not participate in an early detection program using various child development assessments and measures.

Since state context (e.g., policies, guidelines) could also play a role in outcomes for children with autism, this project also examines key state level information to place the findings of the larger study in context. Research personnel conduct interviews with experts in ASD, services, and state policy and ask them open-ended questions to elicit information on barriers and facilitators to early ASD diagnosis, treatment, and outcomes. Experts will also participate in the Delphi panel to use iterative consensus methods to identify the policies that are the most impactful on access to ASD diagnosis outcomes. These findings will be used to create an Autism State Index which is a scale that will quantify a state’s ASD environment, allowing for quantitative analyses.

• Improving the Part C Early Intervention Service Delivery System for Children with ASD: A Randomized Clinical Trial (RISE Study)
Despite strong consensus that early, specialized intervention for children with ASD can have a dramatic impact on outcomes, the U.S. health system’s capacity to provide such services is severely challenged by the rapid rise in ASD prevalence. The long-term goal is to improve outcomes for children with early signs of ASD by increasing the capacity to provide appropriately specialized treatment within an existing infrastructure: the Part C Early Intervention (EI) service delivery system. The study objective is to improve services and outcomes for children with early signs of ASD by conducting a randomized controlled trial (RCT) testing the effectiveness of training EI providers to deliver Reciprocal Imitation Training (RIT). RIT is a naturalistic developmental behavioral intervention (NDBI) that is ideally suited for EI settings because it is low intensity, play-based, easy to learn and implement, and can be taught to families for their independent use, thus increasing intervention dosage. At UMass Chan, research personnel will be involved in the Implementation Aim of the study. This will consist of conducting interviews and data analysis. Research personnel will interview providers and parents involved in the study to understand how the intervention was used. Data regarding provider-initiated modifications to the intervention and delivery will be analyzed to identify fidelity-consistent vs. fidelity-inconsistent changes, which will inform refinement of future RIT training and quality assurance procedures.

• Evaluating Implementation of a Patient Navigator Intervention to Improve Access to Diagnostic and Treatment Services for Children with ASD (K23-Family Navigation Implementation)
Family navigation is a lay-delivered case management strategy designed to reduce health disparities by helping vulnerable populations overcome psychological and logistical hurdles to care. Navigation has proven effectiveness in multiple disorders such as cancer and HIV, and early data support its use as a strategy to promote timely engagement with evidence-based services among children with ASD. However, despite navigation’s substantial effectiveness data, multiple studies demonstrate the attenuation of its impact, and variable success, when implemented in real-world practice. This “research-practice” gap – whereby effective clinical innovations fail to be adopted (or practiced with appropriate fidelity) within real world clinical practice – is ubiquitous in healthcare; but it is particularly problematic for low-income and minority populations and the institutions that serve them. Furthermore, despite guidance to the contrary, few clinical trials proactively collect data on the complex patient, provider, and organizational factors that impact subsequent implementation of the clinical innovations being tested. As a result of this missed opportunity, implementation strategies are often arbitrary and prone to failure. Therefore, this research is to evaluate key implementation processes of family navigation to understand how to improve access to care for low-income children with ASD. This study examines data to better understand the implementation of Family Navigation (FN) and the variability of organizational climate to improve access to diagnosis and treatment for ASD.

• Usability of mHealth Autism Screeners in the Medically Underserved (mHealth ASD Study)
The NIH and the private sector have invested millions of dollars into development of mobile technology-based (mHealth) autism screening tools, with the hope that advanced technologies will improve early identification of ASD. However, no research to date has assessed how mobile device based ASD screening will address the problem of racial, ethnic, language, and income disparities in ASD identification. In addition, no current efforts explicitly assess what key mHealth ASD screener adaptations are needed for mHealth autism screeners to be successfully used by minority and low-income families and the professionals who interact with them. This study examines existing mHealth ASD screeners for overall quality and adaptability to ASD health disparities populations, by comparing them to established mHealth standards. Research staff perform user testing of key tools with a sample of racial/ethnic minority and low-income families and health and educational providers. We conduct interviews with parents, providers, and mHealth ASD screener developers, to understand the challenges of creating and using mHealth ASD screeners in health disparities populations. Finally, we will then use the results of this research, and the guidance of a multi-disciplinary expert panel, to develop a set of guidelines for mHealth autism screener usability in ASD disparities populations. We will disseminate these guidelines throughout the autism research and informatics communities. This research will ensure that the next generation of ASD screening tools effectively reduces disparities in ASD identification.

• Optimizing a Paraprofessional, Family Partner Navigation Model for Children (MOST Study)
Family Navigation (FN) is an evidence-based care management strategy that is a promising intervention to help low-income, diverse families access timely mental health services. Despite significant evidence supporting the effectiveness of FN, concerns exist about the ability to disseminate FN to a broad population due to inefficiency and cost. This study employs an innovative research methodology, the Multiphase Optimization Strategy (MOST), a framework for developing highly efficacious, efficient, scalable, and cost-effective interventions. We are conducting a randomized experiment to assess the individual components of FN and identify which components and component levels have the greatest effect on access to, and engagement in, diagnostic and treatment services for children with mental health disorders. This information will then guide assembly of an optimized FN model that achieves the primary outcomes with least resource consumption and participant burden.