Although the efficacy of early intervention (EI) for autistic children and their families has been established, many marginalized families with diverse cultural and linguistic backgrounds still report inequitable access to evidence-based practices (EBP). The proposed research addresses three aims including: AIM 1. Identify facilitators and barriers of EBP implementation among marginalized families of young autistic children in EI; AIM 2. Develop an implementation toolkit with a focus on capacity building of EI providers to implement EBP with cultural responsiveness; and AIM 3. Examine the feasibility, acceptability, and appropriateness of this toolkit through a pilot trial using RUBI behavioral parent training program.
Patient Population: Adults
Brain maturation in adults with FASD
This application seeks to address gaps in our understanding of fetal alcohol spectrum disorder in adults (FASD) by evaluating protracted effects of prenatal alcohol exposure (PAE) on the brain. Individuals aged 30 and 60, who were diagnosed with FASD in childhood, and matched controls, who had previous structural MRI scans in their teens and twenties will be recruited to have another MRI session in which structural, DTI, and connectivity assessments will be conducted. Comparisons between these and earlier scans will provide insight into the changes in overall brain structure, white matter integrity, and function with age in subjects with alcohol exposure histories. We postulate that brain maturation following PAE follows an altered trajectory relative to normal developing controls.
Patient perspectives on prescribing opioid discontinuation: understanding and promoting safe transitions
A study to verify the clinical benefit of aducanumab in participants with early Alzheimer’s disease (ENVISION)
The primary objective of this study is to verify the clinical benefit of monthly doses of aducanumab in slowing cognitive and functional impairment as measured by changes in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) score as compared with placebo in participants with early Alzheimer’s disease.
A Study of Donanemab in participants with early Alzheimer’s disease (TRAILBLAZER-ALZ 2)
The reason for this study is to see how safe and effective the study drug donanemab is in participants with early Alzheimer’s disease.
Optimizing mental health first-aid programming for sport coaches
Many sport organizations are increasingly vocal about the importance of athlete mental health. Helping organizations move beyond rhetoric to improved athlete wellbeing and safety requires evidence-based resources that are setting-appropriate and feasibly implemented.
This project will develop and obtain feasibility and acceptability data on “Time Out for Mental Health”—a mental health first aid training for sport coaches. This will be accomplished by adapting an existing evidence-based mental health first aid resource to the coach role and sport setting, working closely with a small group of coach partners. The team will focus on ensuring the training is considered useful and feasible by coaches who work in resource deprived school and community-settings given the heightened needs and challenges of youth in such settings, and will train coaches to deliver “Time Out for Mental Health”—to build organizational capacity. “Time Out for Mental Health”—has the potential to strengthen connections between sports organizations and school- and community-based mental health services for millions of adolescents as more than half of high school students play at least one organized school or community sport.
Leveraging artificial intelligence to improve digital mental health interventions
Cognitive therapies help patients by providing ways to modify habitual but unproductive thought patterns, known as maladaptive thinking styles. Cognitive therapies are effective in treating depression, amongst other conditions, and are increasingly delivered remotely as text-based interventions. This trend toward digital delivery has accelerated on account of physical isolation and psychological stressors during the global pandemic. While this means cognitive therapy can potentially reach more patients, the effectiveness of this therapy depends on the ability of a skilled practitioner to recognize types of maladaptive thinking, and there is a critical shortage of mental health practitioners with this expertise.
In radiology, computer-aided diagnosis systems driven by artificial intelligence are used to help physicians detect signs of illness they may otherwise miss. In this project, we will develop a computer-aided detection system to support text-based cognitive therapy. To do so, we will identify indicators of maladaptive thinking styles within a set of text messages exchanged between clients and their therapists, and train neural networks to detect these indicators automatically. The resulting tools will provide a basis for an artificial intelligence-based decision support system to help clinicians recognize and manage maladaptive thinking styles that will enhance the quality and effectiveness of text-based cognitive therapy.
Quantifying socio-cognitive deficits to optimize schizophrenia treatment
Schizophrenia is a debilitating mental health condition with high societal and personal costs, due largely to chronic difficulties with social and occupational functioning. While classical symptoms of schizophrenia – such as hearing voices – are often responsive to medication, people with schizophrenia also experience difficulties in social cognition, or understanding and interpreting the intentions and emotions of others. Social cognition affects the ability to function in society, and is a key determinant of real-world outcomes in schizophrenia.
Despite its importance, we lack objective and easy-to-deploy instruments to assess social cognition. This measurement gap presents a critical stumbling block for development of interventions to improve social cognition, because the effects of potential treatments cannot be assessed efficiently and at high resolution. Better measurements are also needed to identify individuals likely to benefit from such treatments and monitor treatment effects over time.
This project will develop innovative automated methods to measure a key component of social cognition – the ability to recognize the intentions and emotions of others. The underlying idea is to present a participant with a cue – such as a short video clip intended to be amusing – and then apply computational methods to their spoken response to see if it aligns with the intention behind the cue. The result will be a set of validated measurement tools to facilitate objective, repeatable, and scalable assessment of social cognition. These tools will accelerate our ability to rigorously test new treatments targeting these key deficits impacting people living with schizophrenia.
Improving patient-focused, population-informed care in clinical neurosciences
UW Medicine has amassed detailed patient treatment and business data in its electronic medical record (EMR). This information is a treasure trove that is not used to its full potential for two reasons: 1) For each clinical encounter, only a fraction of the information in the EMR is relevant, and virtually all of the information a clinician engages remains in a format that obscures patterns and trends; and 2) In groups of patients with the same illness, data from the EMR could be used to discern larger trends in the course of the disease or evaluate the effect of practice patterns on patient outcomes. The EMR currently does not provide a way to access this information in an agile way.
We have developed innovative software, “Leaf,” that allows medical providers to access population-based EMR data in real time. Leaf is now used at several academic medical centers nationally. In this project, we will collaborate with the UW Memory and Brain Wellness Center to design and evaluate “dashboards” that visualize how a patient’s history and trajectory compare to other, similar patients. For instance, daily function and cognitive testing data for a person with Alzheimer’s disease, already gathered over the course of several years, could be graphed and compared to the same information from all UW patients with Alzheimer’s disease. We will pilot these dashboards in Leaf and collect patient and provider feedback. We intend to publish our results and make code available as part of the open Leaf platform for rapid dissemination.
Noninvasive tracking of intracranial pressure to improve care of traumatic brain injury
Following severe cases of traumatic brain injury (TBI), the brain can swell, leading to elevations in intracranial pressure (ICP). Patients who develop high ICP following severe TBI are more likely to have poor neurologic recovery from their injury, and control of ICP likely contributes to improved outcomes. ICP detection and management is typically guided by invasive monitors placed through the skull and into the injured brain. These devices are highly accurate and reliable, but they are also expensive and expose the patient to rare but potentially serious risks. This is problematic because as few as one-third of patients are found to have elevated ICP, even when the best available evidence is used to guide their placement.
Using ultrasound to measure optic nerve sheath diameter (ONSD) could be an inexpensive, noninvasive and reliable means of monitoring ICP. Located behind the eye, the optic nerve sheath surrounds the nerve carrying visual signals to the brain. Increases in intracranial pressure are transmitted into this conduit, causing it to dilate. Ultrasound-measured ONSD has been shown to correlate with ICP in many neurologic conditions, including TBI, but it has not been systematically evaluated as a screening or a monitoring tool.
This study will routinely measure ONSD in patients undergoing invasive ICP monitoring for severe traumatic brain injury at Harborview Medical Center. The goal is to determine whether ONSD measurement with ultrasound can be combined with readily available clinical data to improve the prediction of elevated ICP, and to assess whether it can be used to monitor ICP during a patient’s hospital stay. If successful, ONSD measurement could have a significant impact on TBI care in both high and low resource settings.
