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:9806296
- 负责人:
- 金额:$ 19.55万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-08-15 至 2024-07-31
- 项目状态:已结题
- 来源:
- 关键词:AccelerometerAdolescenceAdolescentAdultAffectAgitationAndroidAwardBeesBehaviorBiological MarkersBipolar DisorderCaregiversCellular PhoneDataDevelopmentDiagnosticDiurnal RhythmDoctor of PhilosophyEarly InterventionEarly identificationEffectivenessEvaluationExposure toFutureGoalsHealthcareHumanIn SituIndividualInterventionInterviewLearningLifeLinkLongitudinal StudiesMachine LearningMeasuresMental HealthMentored Patient-Oriented Research Career Development AwardMentorsMentorshipMethodsMoodsMorbidity - disease rateNational Institute of Mental HealthNatureOccupationsOutcomeParticipantPatientsPeriodicityPersonsPhenotypePopulationPsyche structurePsychiatryPublic HealthQuality of lifeRecurrenceRelapseReportingResearchResearch DesignResearch PersonnelResourcesRiskSignal TransductionSleepSleep DisordersSpecific qualifier valueSpeechSymptomsTechniquesTechnologyTelephoneTestingTextText MessagingTimeTrainingTranslational ResearchYouthagedbasecareerclinically significantcommon symptomcomputer sciencecostdigitalemerging adultfollow-uphigh riskhigher educationimprovedindexinginnovationmetermobile computingmood symptommortalitynovelnovel strategiespatient orientedpatient oriented researchpredictive modelingpressurepreventprognosticprogramsprospectivescreeningsensorservice utilizationskillssmartphone Applicationsocial
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.
项目总结
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Anna Robinson Van Meter其他文献
Anna Robinson Van Meter的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Anna Robinson Van Meter', 18)}}的其他基金
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
- 批准号:
10582951 - 财政年份:2022
- 资助金额:
$ 19.55万 - 项目类别:
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
- 批准号:
10669716 - 财政年份:2022
- 资助金额:
$ 19.55万 - 项目类别:
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
- 批准号:
10471803 - 财政年份:2022
- 资助金额:
$ 19.55万 - 项目类别:
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
- 批准号:
10214506 - 财政年份:2019
- 资助金额:
$ 19.55万 - 项目类别:
相似海外基金
Identification of Prospective Predictors of Alcohol Initiation During Early Adolescence
青春期早期饮酒的前瞻性预测因素的鉴定
- 批准号:
10823917 - 财政年份:2024
- 资助金额:
$ 19.55万 - 项目类别:
Socio-Emotional Characteristics in Early Childhood and Offending Behaviour in Adolescence
幼儿期的社会情感特征和青春期的犯罪行为
- 批准号:
ES/Z502601/1 - 财政年份:2024
- 资助金额:
$ 19.55万 - 项目类别:
Fellowship
Reasoning about Spatial Relations and Distributions: Supporting STEM Learning in Early Adolescence
空间关系和分布的推理:支持青春期早期的 STEM 学习
- 批准号:
2300937 - 财政年份:2023
- 资助金额:
$ 19.55万 - 项目类别:
Continuing Grant
Cognitive and non-cognitive abilities and career development during adolescence and adult development: from the perspective of genetic and environmental structure
青春期和成人发展期间的认知和非认知能力与职业发展:从遗传和环境结构的角度
- 批准号:
23K02900 - 财政年份:2023
- 资助金额:
$ 19.55万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Does social motivation in adolescence differentially predict the impact of childhood threat exposure on developing suicidal thoughts and behaviors
青春期的社会动机是否可以差异预测童年威胁暴露对自杀想法和行为的影响
- 批准号:
10785373 - 财政年份:2023
- 资助金额:
$ 19.55万 - 项目类别:
Mapping the Neurobiological Risks and Consequences of Alcohol Use in Adolescence and Across the Lifespan
绘制青春期和整个生命周期饮酒的神经生物学风险和后果
- 批准号:
10733406 - 财政年份:2023
- 资助金额:
$ 19.55万 - 项目类别:
Thalamo-prefrontal circuit maturation during adolescence
丘脑-前额叶回路在青春期成熟
- 批准号:
10585031 - 财政年份:2023
- 资助金额:
$ 19.55万 - 项目类别:
The Role of Sleep in the Relationships Among Adverse Childhood Experiences, Mental Health Symptoms, and Persistent/Recurrent Pain during Adolescence
睡眠在不良童年经历、心理健康症状和青春期持续/复发性疼痛之间关系中的作用
- 批准号:
10676403 - 财政年份:2023
- 资助金额:
$ 19.55万 - 项目类别:
Interdisciplinary Perspectives on the Politics of Adolescence and Democracy
青少年政治与民主的跨学科视角
- 批准号:
EP/X026825/1 - 财政年份:2023
- 资助金额:
$ 19.55万 - 项目类别:
Research Grant
Harnessing digital data to study 21st-century adolescence
利用数字数据研究 21 世纪青春期
- 批准号:
MR/X028801/1 - 财政年份:2023
- 资助金额:
$ 19.55万 - 项目类别:
Research Grant