Robust Predictors of Mania and Psychosis

躁狂症和精神病的稳健预测因子

• 批准号: 10571298
• 负责人: JUSTIN T BAKER
• 金额: $ 8.59万
• 依托单位: MCLEAN HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-03 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10571298
• 关键词: Administrative Supplement; Adverse effects; Affective; Behavior; Behavioral; Biological Factors; Bipolar Disorder; COVID-19 pandemic; Cellular Phone; Chronic; Chronic Disease; Clinical; Clinical Data; Communities; Community Networks; Dangerousness; Data; Data Collection; Data Set; Development; Early Intervention; Economic Burden; Environmental Risk Factor; Ethics; FarGo; Fostering; Funding; Genetic Transcription; Goals; Health behavior; Individual; Intervention; Interview; Knowledge; Machine Learning; Manic; Mental disorders; National Institute of Mental Health; Participant; Persons; Pharmaceutical Preparations; Phenotype; Physical environment; Process; Productivity; Psychoses; Psychotic Disorders; Public Health; Quality Control; Research; Research Personnel; Risk; Social Environment; Symptoms; Time; Visualization; Work; base; built environment; data archive; data integration; early psychosis; interest; longitudinal dataset; mental state; multimodal data; multimodality; non-affective psychoses; pandemic disease; parent grant; parent project; predictive test; response; social factors; tool; Administrative Supplement; Adverse effects; Affective; Behavior; Behavioral; Biological Factors; Bipolar Disorder; COVID-19 pandemic; Cellular Phone; Chronic; Chronic Disease; Clinical; Clinical Data; Communities; Community Networks; Dangerousness; Data; Data Collection; Data Set; Development; Early Intervention; Economic Burden; Environmental Risk Factor; Ethics; FarGo; Fostering; Funding; Genetic Transcription; Goals; Health behavior; Individual; Intervention; Interview; Knowledge; Machine Learning; Manic; Mental disorders; National Institute of Mental Health; Participant; Persons; Pharmaceutical Preparations; Phenotype; Physical environment; Process; Productivity; Psychoses; Psychotic Disorders; Public Health; Quality Control; Research; Research Personnel; Risk; Social Environment; Symptoms; Time; Visualization; Work; base; built environment; data archive; data integration; early psychosis; interest; longitudinal dataset; mental state; multimodal data; multimodality; non-affective psychoses; pandemic disease; parent grant; parent project; predictive test; response; social factors; tool

ADMINISTRATIVE SUPPLEMENT PROJECT SUMMARY: This application is an administrative supplement in response to PA-20-272 for a year of extension with funds. The major goals of the supplement are to 1) make data collected and tools developed under the parent grant available to the wider scientific community, and 2) extend data collection in a subset of participants whose data are deemed highly valuable. In Aim 1, we propose to curate 30 multimodal longitudinal (1-year long) datasets to the common format and ethical standard of the National Institute of Mental Health data archive (NDA), including de-identification and transcription of clinical interviews, for sharing with interested investigators in the Intensive Longitudinal Health Behaviors Network (ILHBN) and the wider scientific commnunity. We will also work to disseminate the Deep Phenotyping ToolKit developed under the parent grant, which includes tools for the aggregation and quality control, interactive visualization, and processing of multimodal longitudinal data. In Aim 2, we propose to study 10 select participants for longer than the one-year period designated in the parent grant. The participants will be selected based on having temporally dense multimodal data and fluctuating symptoms. To formalize the process of participant selection, we will develop a tool for forecasting the value of a participant’s longitudinal data, based on data missingness and variance in clinical scores in an initial study period. While the Covid pandemic has had an impact on the parent project, this supplement proposal goes far beyond simply compensating for adverse effects of the pandemic on productivity. The extended goals of the supplement rely on the integration of data and accumulation of knowledge afforded by the parent grant, and could not have been accomplished within the scope of the parent grant. Overall, making multimodal longitudinal datasets, and tools to visualize and process multimodal longitudinal data, available across and beyond the ILHBN community, will maximally leverage the potential of these assets for a broad array of investigators nationally and globally, and will foster the development of common standards for handling longitudinal data. Wider access to high-quality, temporally-dense, behavioral and clinical data in individuals with a mental illness will facilitate and accelerate rigorous computational phenotyping research of severe mental states.

行政补充项目摘要： 该申请是对PA-20-272的响应一年的行政补充 有资金。补充剂的主要目标是1）收集数据并开发了工具 在更广泛科学界的父母赠款下，2）扩展数据收集 在AIM 1中，我们建议策划 30多模式纵向（1年长）数据集达到共同格式和道德标准 美国国家心理健康数据档案馆（NDA），包括去识别和 临床访谈的转录，用于与有趣的调查员分享密集型 纵向健康行为网络（ILHBN）和更广泛的科学界。我们也会 努力传播父母赠款下开发的深层表型工具包 包括用于聚合和质量控制的工具，交互式可视化和处理 多模式纵向数据。在AIM 2中，我们建议研究10位选定参与者的时间比 父母赠款中指定的一年期。参与者将根据 具有暂时密集的多模式数据和波动的符号。正式化过程 选择颗粒，我们将开发一种工具，以预测颗粒的纵向值 数据，基于最初研究期内临床评分的数据丢失和差异。 虽然COVID大流行对父母项目产生了影响，但该补充提案 仅仅弥补了大流行对生产力的不利影响远远不止。这 补充的扩展目标取决于数据的整合和知识的积累 父母赠款提供的，无法在父母的范围内完成 授予。总体而言，制作多模式纵向数据集和可视化和处理的工具 在ILHBN社区跨越跨越的多模式纵向数据将最大 利用这些资产的潜力为全国和全球广泛的调查人员 并将促进处理纵向数据的共同标准。更广泛的访问 患有精神疾病的个体的高质量，暂时密集，行为和临床数据 将促进并加速严格的严重精神计算表型研究 国家。