Methodological Development

方法论发展

• 批准号: 10267121
• 负责人: Laura Koehly
• 金额: $ 19.75万
• 依托单位: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10267121
• 关键词: Address; Area; Behavioral Sciences; Cancer Patient; Clinic; Collaborations; Communication; Data; Development; Disease Outbreaks; Evaluation; Family; Hereditary Disease; Hospitals; Infection; Inpatients; Manuscripts; Measurement; Measures; Methodology; Methods; Modeling; Nosocomial Infections; Paper; Psychometrics; Publishing; Recording of previous events; Reporting; Research; Resources; Risk; Science; Social Environment; Social Network; Social Sciences; System; Testing; Time; Work; caregiving; chemotherapy; design; disorder risk; improved; indexing; informant; instrument; method development; mortality; novel; research and development; social; stem; tool

During the current reporting period, we developed and employed novel methods aimed at measuring, describing and modeling social networks. We continue to develop a framework for the psychometric evaluation of multiplex networks measuring a common relational construct. By multiplexity, we mean how different types of relationships overlap. This new research provides a general approach to modeling multivariate network systems addressing both questions about construct measurement and questions that consider the complexity of social systems that inherently involve multiple types of resource exchanges. We recently published the manuscript stemming from this work. In collaboration with Lise Getoor's lab, we have developed a computational approach for reconciling network data obtained through a multi-informant design. A paper describing and comparing various computational approaches was recently published. As well, we have demonstrated how the use of multi-informant approaches to family history assessment can potentially improve risk evaluations in the clinic. In addition, new research has examined how co-presence metrics derived from hospital administrative data can be used as an "index test" to predict nosocomial infection, identify inpatients who are subclinically infected, and to evaluate the impact of social influence on mortality in cancer patients receiving chemotherapy in an open setting. Novel metrics of co-presence have been developed, including a measure of consistent co-presence and co-presence thresholds that represent critical windows that increase the likelihood of infection during outbreaks of hospital born infections. During the reporting period, two manuscripts have been published, and one manuscript is being finalized for submission.

在本报告所述期间，我们开发并采用了旨在衡量、描述和模拟社会网络的新方法。我们继续开发一个框架，用于测量一个共同的关系结构的多个网络的心理测量评估。我们所说的多元化，是指不同类型的关系如何重叠。这项新的研究提供了一种建模多变量网络系统的一般方法，既解决了关于构造测量的问题，也提供了考虑固有地涉及多种类型的资源交换的社会系统的复杂性的问题。我们最近发表了源于这部作品的手稿。 与Lise GToor的实验室合作，我们开发了一种计算方法，用于协调通过多信息者设计获得的网络数据。最近发表了一篇描述和比较各种计算方法的论文。此外，我们还展示了如何使用多信息者方法评估家族史可以潜在地改善诊所的风险评估。 此外，新的研究还研究了如何将来自医院管理数据的共存指标用作预测医院感染、识别亚临床感染的住院患者以及评估在开放环境下接受化疗的癌症患者的社会影响对死亡率的影响的“指数测试”。已经开发了共存的新指标，包括测量一致的共存和共存阈值，这些阈值代表在医院出生感染暴发期间增加感染可能性的关键窗口。在本报告所述期间，已经出版了两份手稿，其中一份手稿正在定稿以供提交。