Over 65% of people who are incarcerated have a substance use disorder (SUD). Many jails and prisons provide substance use treatment, including behavioral and pharmacotherapy, and SUD identification is the first step. Prisons and jails are a distinct setting for SUD assessment, and tools used for SUD screening in community settings may not perform the same way in carceral settings. This systematic review will identify psychometric evaluation studies in carceral settings of screening and diagnostic tools for SUDs, generally, or specific SUDs (excluding alcohol and nicotine). Additionally, will use and adapt an existing clinical usability scale and develop new metrics to assess acceptability of screening tool use in carceral settings for a person-centered evaluation. This will be guided by further analysis of interviews with prison staff and people with lived experience of incarceration. The additional assessments will capture potential barriers and facilitators to SUD assessment in jails and prisons as they represent resource-limited settings with unique challenges compared to other health systems. The goals for the study are: 1) to help carceral facilities make informed decisions about SUD assessment, 2) to reveal key gaps in the literature, and 3) to inform the development and testing of future tools.
Funding Type: State/UW
Improving risk-stratification of substance-induced psychosis: incorporating stakeholder perspectives and implementing a standardized assessment of risk factors
First-episode substance-induced psychosis (SIP) presents a clinical challenge in which treatment decisions cannot rely on evidence-based guidelines and long-term outcomes are not well understood. Preliminary findings from our retrospective study of psychiatry inpatients at Harborview Medical Center (HMC) suggest that patients with first-episode SIP had similar rehospitalization rates to those with first-episode psychosis (FEP) but were less likely to receive long-acting injectable antipsychotics (LAIs) even though LAIs may reduce the risk of 30- and 180-day rehospitalization. Our study has also revealed inconsistent assessment of key risk factors for rehospitalization—such as family history of psychosis and patterns of cannabis use—that may be limiting informed decision-making, including appropriate LAI use. This project seeks to improve the risk stratification of first-episode SIP by addressing these gaps. Aim 1 will use qualitative interviews with inpatient attending psychiatrists, psychiatry residents, and patients to explore factors influencing the management of first-episode SIP. Aim 2 will evaluate the acceptability and feasibility of implementing a standardized assessment of cannabis use and family history of psychosis on HMC inpatient psychiatry units. This project will lay the groundwork for future clinical interventions that optimize treatment decisions and improve patient outcomes in psychiatric inpatient settings.
Unraveling the genetics of schizophrenia and bipolar disorder with large-language models
Schizophrenia (SCZ) and bipolar disorder (BPD) are among the most heritable psychiatric conditions, yet their genetic foundations remain poorly understood. Historically, unraveling these disorders’ genetic architectures was limited by inadequate technology. However, breakthroughs in next-generation sequencing have recently produced expansive genomic datasets—including those from the Psychiatric Genomics Consortium (PGC)—for SCZ and BD. Simultaneously, genomic foundation models—advanced large-language models (LLMs) trained on biological data rather than corpuses of text—have emerged as next-generation artificial intelligence platforms that offer unparalleled abilities to predict the functional effects of genetic variants, many of which were previously unclassified. This proposal harnesses these models to analyze publicly available PGC genomic datasets, aiming to annotate both common and rare genetic variants associated with SCZ and BD, pinpoint disease-associated genes, and map the biological pathways they influence. By bridging these recent advances in artificial intelligence with robust genomic data, this proposal seeks to illuminate the genetic underpinnings of SCZ and BPD. The anticipated insights promise to deepen our understanding of heritable psychiatric conditions, laying the groundwork for enhanced diagnostics and novel therapies aimed at biology, rather than nosology
Psychomotor function of Locus Coeruleus-Norepinephrine system during decision-making
Many psychiatric disorders involve an abnormality in movements, termed ‘psychomotor’
dysfunction, that reflects aberrant activity of the brain circuits producing behavior. Nevertheless,
psychomotor mechanisms remain poorly understood. One possible source of psychomotor dysfunction is alterations in neuromodulatory transmitters, such as norepinephrine (NE), which is broadcast throughout the brain from a small brainstem region called locus coeruleus (LC). LC-NE is implicated in psychiatric disorders including depression, PTSD, ADHD, and dementia, with behavioral neuroscience studies demonstrating roles in arousal and decision-making. LC-NE is often studied in psychiatry on the timescale of minutes to hours with a focus on NE drugs, leaving underexamined the precise temporal relationship between LC neural activity and discrete components of motivated behavior. This proposal aims to identify psychomotor functions of LC-NE in decision-making at the level of neural circuit activity in mice. We leverage powerful techniques to record LC neural activity with high spatiotemporal precision while simultaneously deploying advances in AI machine vision technology to quantify the mouse’s movements. By precisely quantifying movement patterns and LC-NE activity, we aim to characterize basic psychomotor functions related to cognition. In turn, our work will build a foundation for noninvasive, mechanistic biomarkers that enhance the diagnosis and management of psychiatric disorders.
Once-weekly GLP-1R agonist dulaglutide for treatment of fentanyl use disorder and modulation of lateral habenula activity in male and female rats
Current pharmacological treatments for fentanyl use disorder, primarily opioid replacements, have proven insufficient to stem the tide of fentanyl related suffering and deaths. Novel pharmacotherapies are desperately needed, ideally ones that are non-opioid, highly convenient, and produce minimal side effects. One promising class of drugs that meets these criteria are glucagon-like peptide 1 (GLP-1) receptor (GLP-1R) agonists. Endogenous GLP-1 is released in response to food intake, but GLP-1Rs are present in many tissues throughout the body, including brain regions involved in addiction. Early studies have shown GLP-1R agonists may reduce drug seeking. Here, we aim to determine if the long acting GLP-1R agonist dulaglutide, given once weekly, can reduce fentanyl SA for a substantial period of time (3 weeks), even after SA has been established.
Enhancing Suicide Care Monitoring and Intervention in Primary Care
This project outlines a comprehensive two-year initiative aimed at enhancing suicide care services in primary care settings. The project addresses a critical gap in the continuum of care by providing interim crisis support for at-risk patients who are waiting to be connected to specialty mental health. The main objectives of this project are to develop two innovative interventions intended to be delivered in a primary care setting: an adapted caring contacts protocol and a system to provide short-term, centralized remote monitoring of patient’s suicide risk. In designing these interventions, we intend to leverage technology such as digital/online platforms and remote monitoring systems that will support asynchronous patient check-ins. Finding innovative ways to offer support to patients in primary care settings where there is limited clinician time and typically an even more limited behavioral health workforce is imperative to creating a sustainable program. Therefore, our proposal intends to maximize the use of technology and focuses on self-guided and/or automated approaches.
This project uses a co-design approach to develop these interventions, where we will elicit input directly from patients and caregivers on the acceptability, feasibility, and appropriateness of these interventions. We hope this project will improve the timely support and management of suicide risk among primary care patients, ultimately enhancing services in outpatient settings while supporting the Least Restrictive Environment Framework, to enhance patient outcomes, reduce unnecessary referrals to overburdened emergency departments, and promote the overall well-being of patients and their families.
Adaptation and co-design of a digital intervention for suicide prevention in primary care
Suicide is a leading cause of death among 10-to-24-year-olds. Primary Care (PC) often serves as a trusted resource for adolescents and young adults (AYA) and their families; and routine wellness visits provide important opportunities for early detection of suicide risk. Importantly, nearly half of those who die by suicide contact their PC clinic within one month prior to suicide. Unfortunately, suicide prevention resources for PC are limited, with a particular gap in short-term risk management and intervention services for lower risk patients and patients with STB who are waiting to be connected to specialty mental health care. Furthermore, parents/caregivers (hereafter referred to as parents) represent a key protective factor for suicidal AYA. Yet, few interventions have been developed to leverage parent support and increase parental self-efficacy to prevent AYA suicide. The current project partners with a digital mental health app, iKinnect, to adapt it for use in PC. iKinnect is designed to improve parent and AYA communication and parental selfefficacy to prevent risk behaviors, including suicide behaviors. The tool uses a parent and AYA paired interface and was originally designed for implementation with high-risk youth involved in the juvenile justice system. Intervention components include parent and AYA content including safety planning, skills for emotion management, parent coaching on lethal means restriction, expectation and goal setting, earning/providing rewards and praise, and modeling videos for parents. While promising, the program has yet to be tested with AYA presenting with suicide risk in PC.
Default mode network impairments in comorbid anxiety and cannabis use disorders
Social anxiety disorder (SAD) is characterized by maladaptive self-focused attention (SFA), which itself is correlated with large scale brain network connectivity impairments. Cannabis use disorder (CUD) is commonly conceptualized as impaired reward processing within the ventral dopaminergic network, however, it is also implicated in connectivity disturbances in other critical cortical circuits. In the current study we will characterize the large scale brain network impairment in comorbid SAD and CUD given commonly overlapping symptoms and population prevalence
Psychosis beyond symptoms: Cognitive and genetic biomarkers of schizophrenia
Schizophrenia is a prevalent, debilitating psychiatric disorder that is diagnosed based on clinical interviews that are subjective and highly variable; in fact, two patients can have no overlapping symptoms and be diagnosed with the same disease. While cardiologists have blood tests to help diagnose heart attacks and oncologists have PET scans to find hidden cancers, psychiatrists don’t have objective diagnostic tests. This proposal will utilize machine learning to analyze cognitive tests, brain electrical activity, and genetic signatures from 1,415 patients with schizophrenia and 1,062 controls to uncover biomarkers of schizophrenia. By incorporating biomarkers into diagnostic standards, psychiatrists could one day order a simple test that could help them confidently diagnose schizophrenia and make better treatment decisions based on quantitative rather than subjective measures.
Exploring the implementation determinants of paraprofessional task-shared mental roles in integrated behavioral care settings in Washington State
The gap between the number of people needing and accessing mental health care has led to the development of new types of mental health providers to help expand access to care. These providers, referred to as paraprofessionals, have typically at most a bachelor’s degree and treat mild and moderate depression and anxiety. However, because the novelty of these roles in the Unites States, little is known about organizational and employee barriers to uptake and implementation. Further, little is known about US patient perspectives on having a paraprofessional mental health provider. The proposed research explores behavioral health employer, behavioral health employee, and patient perspectives on two new paraprofessional roles being deployed in Washington State – the mental health Community Health Worker and the Behavioral Health Support Specialist – to help identify key barriers and facilitators to implementation of these roles.
