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The Digital Phenotype of Bipolar Disorder: Harnessing Technology to Identify Bipolar Mood Symptoms

双相情感障碍的数字表型：利用技术识别双相情感障碍的症状

基本信息

批准号：
10669716
负责人：
Anna Robinson Van Meter
金额：
$ 19.55万
依托单位：
NEW YORK UNIVERSITY SCHOOL OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-03-04 至 2024-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10669716
关键词：
Accelerometer Adolescence Adolescent Adult Affect Agitation Android Award Bees Behavior Biological Markers Bipolar Disorder Caregivers Cellular Phone Data Development Diagnostic Digital biomarker Diurnal Rhythm Doctor of Philosophy Early Intervention Early identification Effectiveness Evaluation Exposure to Future Goals Human In Situ Individual Intervention Interview Learning Life Life Expectancy Link Longitudinal Studies Measures Mental Health Mental Health Services Mentored Patient-Oriented Research Career Development Award Mentors Mentorship Meta-Analysis Methods Moods Morbidity - disease rate National Institute of Mental Health Nature Occupations Outcome Participant Patients Periodicity Persons Phenotype Population Psyche structure Psychiatry Psychotic Disorders Public Health Quality of life Recurrence Relapse Reporting Research Research Design Research Personnel Resources Risk Signal Transduction Sleep Sleep Disorders Specific qualifier value Speech Symptoms Techniques Technology Telephone Testing Text Messaging Time Training Translational Research Validity and Reliability Youth aged career clinically significant common symptom computer science cost digital emerging adult follow-up high risk higher education improved indexing innovation longitudinal analysis meter mobile computing mood symptom mortality new technology novel strategies patient oriented patient oriented research predictive modeling pressure prevent prognostication programs prospective screening sensor service utilization skills smartphone application social statistical and machine learning statistical learning

项目摘要

Project Summary Bipolar disorder (BD) is associated with significant mortality and morbidity. It typically begins in adolescence or early adulthood, an important developmental period during which higher education, first jobs, and relationships are pursued. Recurrent mood episodes during this period can have a devastating impact on a young person's ability to achieve a high quality of life as an adult. A method by which to predict the onset of mood symptoms in adolescence would create an opportunity to intervene and reduce exposure to the harmful effects of recurrent episodes. A new approach – digital phenotyping – may make this possible. Digital phenotyping is defined as the “moment-by-moment quantification of the human phenotype in situ” using data collected from smartphone sensors (accelerometer, texts, calls, GPS). Digital phenotyping has been used to identify mood changes and potential signs of relapse in adults with BD, but has not yet been applied to adolescents. We will use Beiwe, a digital phenotyping application for iOS and Android phones, to collect digital phenotypes from participants (aged 14-19) over 18-months (N=120; n=70 with BD [I, II, Other Specified], n=50 typically-developing). Over the follow-up period, participants will complete biweekly mood assessments, and both participants and caregivers will be interviewed monthly to track changes in mood/behavior. This will allow the phone sensor data collected with Beiwe to be closely linked to symptom changes. The specific aims of this project are (1) to characterize the digital phenotype of BD symptoms in adolescents, (2) to describe differences in the digital phenotypes of the BD and typically developing groups, and (3) to develop a model for predicting mood symptoms prospectively. The proposed study is consistent with all four NIMH strategic objectives for the future of mental health research. This K23 Award will provide Anna Van Meter, PhD with the necessary training and mentorship to (1) gain proficiency in computational psychiatry by learning to analyze longitudinal data using statistical and machine learning techniques, (2) build expertise in patient-oriented translational research by designing and conducting a longitudinal study with youth participants; (3) learn to employ state-of-the-art mobile technology to personalize assessment and intervention using patient data. To accomplish these training goals, Dr. Van Meter has organized an outstanding mentorship team (Anil Malhotra, MD, Jukka-Pekka Onnela, DSc, John Kane, MD, Christoph Correll, MD, and Deborah Estrin, PhD), with expertise in patient-oriented research, technology-based mental health research, computational psychiatry, bipolar disorder in youth, and computer science. The proposed study will be the first to describe the digital phenotype of BD in adolescents, a population at great risk for the onset of BD as well as the damaging effects of repeated episodes. The completion of the proposed K23 Mentored Career Award will support an innovative program of patient-oriented research, and will provide Dr. Van Meter with the skills necessary to become an independent investigator pursuing novel technological solutions to improve patients' quality of life.

项目摘要双相情感障碍(BD)与显著的死亡率和发病率有关。它通常开始于青春期或成年早期，这是一个重要的发展时期，在这段时期里，高等教育、第一份工作和人际关系都在追捕。在此期间反复出现的情绪发作可能会对年轻人的作为成年人实现高质量生活的能力。一种预测心境症状发生时间的方法青春期将创造机会进行干预，减少接触反复发作的有害影响。剧集。一种新的方法--数字表型--可能使这成为可能。数字表型的定义是利用智能手机采集的数据对人的表型进行“现场逐点量化” 传感器(加速计、短信、电话、GPS)。数字表型已被用来识别情绪变化和在患有BD的成年人中有潜在的复发迹象，但尚未应用于青少年。我们将使用北威，一个用于iOS和Android手机的数字表型应用程序，用于收集参与者的数字表型 (14-19岁)18个月以上(N=120；n=70伴BD[I，II，其他规定]，n=50典型发展)。完毕在随访期，参与者将完成每两周一次的情绪评估，参与者和照顾者将每月接受采访，以跟踪情绪/行为的变化。这将允许电话传感器与贝威一起收集的数据将与症状变化密切相关。该项目的具体目标是：(1) 描述青少年BD症状的数字表型，(2)描述数字表型的差异 BD的表型和典型的发育群体，以及(3)开发一个预测情绪的模型前瞻的症状。拟议的研究与NIMH未来的所有四个战略目标一致心理健康研究方面的专家。这项K23奖将为安娜·范·米特博士提供必要的培训和指导：(1)通过学习分析纵向数据，精通计算精神病学。统计和机器学习技术，(2)通过以下方式在面向患者的翻译研究中积累专业知识设计并与青年参与者一起进行纵向研究；(3)学习使用最先进的技术使用患者数据进行个性化评估和干预的移动技术。为了完成这些培训 Van Meter博士组织了一支杰出的导师团队(Anil Malhotra，医学博士，Jukka-Pekka Onnela， DSC、John Kane医学博士、Christoph Correll医学博士和Deborah Estrin博士)，具有以患者为导向的专业知识研究，以技术为基础的精神健康研究，计算精神病学，青年双相情感障碍，以及计算机科学。这项拟议的研究将首次描述青少年BD的数字表型， BD发病风险很大的人群以及反复发作的破坏性影响。这个完成拟议的K23指导职业奖将支持一个以患者为导向的创新计划研究，并将为Van Meter博士提供成为独立调查员所需的技能寻求新的技术解决方案，提高患者的生活质量。

项目成果

期刊论文数量（17）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Clinician Perspectives on Using Computational Mental Health Insights From Patients' Social Media Activities: Design and Qualitative Evaluation of a Prototype.

DOI：
10.2196/25455
发表时间：
2021-11-16
期刊：
JMIR mental health
影响因子：
5.2
作者：
Yoo DW;Ernala SK;Saket B;Weir D;Arenare E;Ali AF;Van Meter AR;Birnbaum ML;Abowd GD;De Choudhury M
通讯作者：
De Choudhury M

The Impact of the COVID-19 Pandemic on Adolescents: An Opportunity to Build Resilient Systems.

COVID-19 大流行对青少年的影响：构建弹性系统的机会。

DOI：
10.1177/08901171221140641d
发表时间：
2023
期刊：
American journal of health promotion : AJHP
影响因子：
0
作者：
Nadeem,Erum;RVanMeter,Anna
通讯作者：
RVanMeter,Anna

Pramipexole to Improve Cognition in Bipolar Disorder: A Randomized Controlled Trial.

DOI：
10.1097/jcp.0000000000001407
发表时间：
2021-07-01
期刊：
Journal of clinical psychopharmacology
影响因子：
2.9
作者：
Van Meter AR;Perez-Rodriguez MM;Braga RJ;Shanahan M;Hanna L;Malhotra AK;Burdick KE
通讯作者：
Burdick KE

The stability and persistence of symptoms in childhood-onset ADHD.

儿童期多动症症状的稳定性和持续性。

DOI：
10.1007/s00787-023-02235-3
发表时间：
2024
期刊：
European child & adolescent psychiatry
影响因子：
6.4
作者：
VanMeter,AnnaR;Sibley,MargaretH;Vandana,Pankhuree;Birmaher,Boris;Fristad,MaryA;Horwitz,Sarah;Youngstrom,EricA;Findling,RobertL;Arnold,LEugene
通讯作者：
Arnold,LEugene

Associations of Social Capital with Mental Disorder Prevalence, Severity, and Comorbidity among U.S. Adolescents.