The Center for Enhancing Treatment and Utilization for Depression and Emergent Suicidality (ETUDES) in Pediatric Primary Care

儿科初级保健中抑郁症和紧急自杀加强治疗和利用中心 (ETUDES)

• 批准号: 10631205
• 负责人: David A. Brent
• 金额: $ 323.88万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-17 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10631205
• 关键词: 19 year old; Address; Adolescent; Anhedonia; Attention; Black Populations; Black race; Caregivers; Caring; Cause of Death; Childhood; Clinical; Clinical Trials; Collaborations; Communities; Complement; Consultations; Data; Detection; Development; Education; Electronic Health Record; Emergency Situation; Event; Family; Feeling suicidal; Funding; Health Services Accessibility; Healthcare; Individual; Intervention; Leadership; Literature; Longitudinal Studies; Machine Learning; Mediator; Mental Depression; Mental Health; Mental Health Services; Mentorship; Methods; Mission; Monitor; Outcome; Pathway interactions; Patient Preferences; Patient Self-Report; Patients; Physicians; Play; Population Heterogeneity; Predictive Analytics; Prevention; Primary Care; Probability; Public Health; Publications; Randomized, Controlled Trials; Recommendation; Records; Research; Research Training; Resources; Risk; Risk Factors; Role; Safety; Sampling; Scientist; Services; Sleep Disorders; Source; Suicide; Suicide attempt; Suicide prevention; Teenagers; Testing; Training; Victimization; Visit; Work; Youth; access disparities; adolescent suicide; aged; career; child depression; cohort; depression prevention; disparity reduction; effectiveness testing; electronic health data; experience; health disparity; health equity; high risk; high-risk adolescents; implementation science; improved; integrated care; machine learning algorithm; mobile sensing; novel; pediatrician; poor sleep; prediction algorithm; predictive modeling; prevent; primary care provider; primary care setting; racial disparity; recruit; reducing suicide; risk prediction; routine screening; screening; suicidal; suicidal adolescent; suicidal behavior; suicidal risk; suicide rate; symposium; therapy design; therapy development; tool; treatment as usual; trial comparing

This application for a Practice-based Suicide Prevention Center (PAR-20-286), ETUDES (Enhancing Treatment and Utilization for Depression and Emergent Suicidality) is a competitive renewal of our current Alacrity P50. We aim to address the crisis in adolescent suicide, with special attention to Black youth, for whom the rate of suicide attempts has increased more rapidly than in any other demographic group. We will develop and test effective methods for identifying and intervening with youth at risk for suicide that can be readily deployed in pediatric primary care (PPC). We focus on PPC because most youth visit PPC annually, youth are routinely screened annually for depression and suicidal risk, and mental health treatment delivered in primary care can decrease disparities in access and outcomes. We focus on the following strategies to reduce suicidal behaviors: (1) improved identification to complement screening; (2) promote linkages to services and safety planning; and (3) targeting risk factors for depression and suicidality to prevent the onset of suicidal crises. In the first component of our signature R01, we will develop prediction models that combine machine learning algorithms using EHR data and mobile sensing to improve our detection of imminent suicidal risk in a cohort of 2,000 youth, recruited from PPC. In the 2nd component of the R01, we will conduct a randomized controlled trial on a subset of this cohort, 900 suicidal youth, comparing usual care to a suite of tools that we have developed to help PPC providers assess and manage suicidal youth. In previous work, these tools increased physician referrals to mental health and engagement in treatment, and reduced suicidal behavior. We propose three R34s that target domains that increase risk for depression and suicidality, namely, online victimization, low activity/anhedonia, and poor sleep. To address the national crisis of rising suicidal behavior in Black youth, we will recruit a sample that is at least 35% Black, and apply implementation science methods to ensure that all assessments and interventions are acceptable and effective for Black youth and their families. Moreover, our methods of identification and interventions target probable sources of racial disparities in suicidal behavior, namely, treatment access, online victimization, low activity, and poor sleep. This Center renewal convenes a diverse, interdisciplinary team, with expertise in clinical trials and longitudinal studies, machine learning, mobile sensing, health disparities, and implementation science. All aims are guided by collaboration with stakeholders, some of whom play leadership roles in the Center. Primary to the Center’s mission is the training and support of a diverse group of 10 early career scientists who play critical roles in Center projects. If successful, Center projects should yield predictive algorithms for imminent suicidal risk to complement annual screening, a care pathway for suicidal adolescents that can be implemented in PPC and will substantially reduce suicide-related events, and interventions to prevent depression and suicidal behavior. These tools aim to reduce racial disparities in suicidal behavior by improving identification, and access, and by targeting risk factors that are more prevalent among Black youth.

本申请为一个基于实践的自杀预防中心（PAR-20-286），ETUDES（加强治疗 和抑郁症和紧急自杀的利用）是我们目前的敏捷P50的竞争性更新。我们 旨在解决青少年自杀危机，特别关注黑人青年，他们的自杀率 尝试增加的速度比任何其他人口群体都要快。我们将开发和测试有效的 识别和干预有自杀风险的青少年的方法， 初级保健（PPC）。我们专注于PPC，因为大多数年轻人每年都会访问PPC， 抑郁症和自杀风险，在初级保健中提供的心理健康治疗可以减少 在获得机会和结果方面的差距。我们专注于以下策略来减少自杀行为：（1） （2）促进与服务和安全规划的联系;（3） 针对抑郁症和自杀倾向的风险因素，预防自杀危机的发生。第一组分中 我们的签名R 01，我们将开发预测模型，结合联合收割机机器学习算法使用EHR 数据和移动的传感，以提高我们对2,000名年轻人的迫在眉睫的自杀风险的检测， 从PPC。在R 01的第二部分中，我们将对其中的一个子集进行随机对照试验。 队列，900自杀青年，比较常规护理，我们已经开发了一套工具，以帮助PPC提供者 评估和管理自杀青年。在以前的工作中，这些工具增加了医生对心理健康的转诊 积极参与治疗，减少自杀行为。我们提出了三个R34的目标领域， 抑郁和自杀风险增加，即网上受害、低活动/快感缺乏和睡眠不良。 为了解决黑人青年自杀行为上升的国家危机，我们将招募一个样本， 35%的黑人，并应用实施科学方法，以确保所有评估和干预措施 对黑人青年及其家庭来说是可以接受的和有效的。此外，我们的识别方法和 干预措施针对自杀行为中种族差异的可能来源，即治疗途径、在线 受害，低活动，睡眠不好。该中心的更新召集了一个多元化的跨学科团队， 在临床试验和纵向研究、机器学习、移动的传感、健康差异和 执行科学。所有目标都是通过与利益相关者的合作来指导的，其中一些利益相关者发挥了领导作用。 中心的角色。该中心的主要使命是培训和支持一个由10名早期 在中心项目中发挥关键作用的职业科学家。如果成功，中心项目应产生预测性 即将发生自杀风险的算法，以补充年度筛查，这是自杀青少年的护理途径 可以在PPC中实施，并将大大减少自杀相关事件， 抑郁和自杀行为。这些工具旨在通过改善自杀行为来减少种族差异。 识别和获取，并针对黑人青年中更普遍的风险因素。

项目成果

A protocol for applying health equity-informed implementation science models and frameworks to adapt a sleep intervention for adolescents at risk for suicidal thoughts and behaviors.

• DOI: 10.3389/fpubh.2022.971754
• 发表时间: 2022
• 期刊: FRONTIERS IN PUBLIC HEALTH
• 影响因子: 5.2
• 作者: Williamson, Ariel A. A.;Soehner, Adriane M. M.;Boyd, Rhonda C. C.;Buysse, Daniel J. J.;Harvey, Allison G. G.;Jonassaint, Charles R. R.;Franzen, Peter L. L.;Goldstein, Tina R. R.
• 通讯作者: Goldstein, Tina R. R.

Commentary: Reducing adolescent suicide: a global imperative - a reflection on Glenn et al. (2020).

评论：减少青少年自杀：全球势在必行——对格伦等人的反思。

• DOI: 10.1111/jcpp.13174
• 发表时间: 2020
• 期刊: Journal of child psychology and psychiatry, and allied disciplines
• 作者: Brent,DavidA

A Comprehensive Review of the Literature on Sleep Difficulties and Suicidality in Youth to Inform an Integrative Developmental Model and Future Directions.

• DOI: 10.1007/s40675-022-00222-9
• 发表时间: 2022-03
• 期刊: CURRENT SLEEP MEDICINE REPORTS
• 影响因子: 1.8
• 作者: Goldstein, Tina R;Franzen, Peter L
• 通讯作者: Franzen, Peter L

Preliminary analysis of low-level alcohol use and suicidality with children in the adolescent brain and cognitive development (ABCD) baseline cohort.

• DOI: 10.1016/j.psychres.2021.113825
• 发表时间: 2021-05
• 期刊: Psychiatry research
• 影响因子: 11.3
• 作者: Aguinaldo LD;Goldstone A;Hasler BP;Brent DA;Coronado C;Jacobus J
• 通讯作者: Jacobus J

Predicting Depression in Adolescents Using Mobile and Wearable Sensors: Multimodal Machine Learning-Based Exploratory Study.

• DOI: 10.2196/35807
• 发表时间: 2022-06-24
• 期刊: JMIR FORMATIVE RESEARCH
• 影响因子: 2.2
• 作者: Mullick, Tahsin;Radovic, Ana;Shaaban, Sam;Doryab, Afsaneh
• 通讯作者: Doryab, Afsaneh