SCH: INT: Collaborative Research: Passive sensing of social isolation: A digital phenotying approach

SCH:INT:协作研究:社会隔离的被动感知:数字表型方法

基本信息

项目摘要

Social isolation-including both the objective phenomenon of 'aloneness' and the subjective experience of loneliness (perceived isolation)-is a major problem globally. Our goal in the proposed project is to capitalize on statistical methods for harnessing the power of smartphone-based measurement of continuous, unobtrusive, and real-time assessment of social isolation. We bring together a team of clinical scientists with expertise in social behavior dynamics, engineers/computer scientists at the forefront of research on digital signal processing, and biostatisticians with expert knowledge in passive sensing technology to provide robust methodological rigor needed to execute the study's aims. Using a digital phenotyping approach (i.e., the moment-by-moment quantification of the individual-level human phenotype in situ using data from personal smartphones), we will develop and test algorithms that incorporate both active (ecological momentary assessment) and passive (movement, location, conversation) metrics to improve characterization and prediction of social isolation. We will then conduct a preliminary evaluation of the promise of a dynamic network analysis of social isolation transition states, followed by application of this approach to a clinical sample characterized by social isolation. RELEVANCE (See instructions): Findings from this project will have far-reaching application to global health, as our·emerging understanding of social isolation as a key contributor to early mortality and other significant health problems highlights the need for a scalable, comprehensive, and personalized assessment and intervention approach. Developing new methods for improving inference of social behavior from temporally-dense smartphone data will benefit an expanding area of research in digital health. This contribution extends beyond the applied aims of the project, as the methodological advancements we will develop can be applied to a large corpus of existing data and future projects. Ultimately, this work will inform the delivery of sustainable interventions targeting social isolation in ieal- time and in daily contexts.
社会孤立——包括“孤独”的客观现象和孤独的主观体验

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)

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Carlos Alberto Busso其他文献

Level of habitat fragmentation determines its non-linear relationships with plant species richness, frequency and density at desertified grasslands in Inner Mongolia, China
内蒙古荒漠化草原生境破碎化程度决定了其与植物物种丰富度、频率和密度的非线性关系
  • DOI:
    10.1093/jpe/rtx050
  • 发表时间:
    2018-12
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zhimin Liu;Wenkai Shou;Jianqiang Qian;Jing Wu;Carlos Alberto Busso;Xianzhang Hou
  • 通讯作者:
    Xianzhang Hou
Germination of <em>Larrea divaricata Cav</em>, an important shrub species to restore desertified arid ecosystems
  • DOI:
    10.1016/j.jaridenv.2020.104175
  • 发表时间:
    2020-08-01
  • 期刊:
  • 影响因子:
  • 作者:
    Jorge Ariel Hernandez;Daniel Roberto Pérez;Carlos Alberto Busso
  • 通讯作者:
    Carlos Alberto Busso

Carlos Alberto Busso的其他文献

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{{ truncateString('Carlos Alberto Busso', 18)}}的其他基金

SCH: INT: Collaborative Research: Passive sensing of social isolation: A digital phenotying approach
SCH:INT:协作研究:社会隔离的被动感知:数字表型方法
  • 批准号:
    9929244
  • 财政年份:
    2019
  • 资助金额:
    $ 28.05万
  • 项目类别:
SCH: INT: Collaborative Research: Passive sensing of social isolation: A digital phenotying approach
SCH:INT:协作研究:社会隔离的被动感知:数字表型方法
  • 批准号:
    10245222
  • 财政年份:
    2019
  • 资助金额:
    $ 28.05万
  • 项目类别:
SCH: INT: Collaborative Research: Passive sensing of social isolation: A digital phenotying approach
SCH:INT:协作研究:社会隔离的被动感知:数字表型方法
  • 批准号:
    10022338
  • 财政年份:
    2019
  • 资助金额:
    $ 28.05万
  • 项目类别:

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