Bayesian Methods for a Longitudinal CAT

纵向 CAT 的贝叶斯方法

• 批准号: 7640794
• 负责人: RICHARD SWARTZ
• 金额: $ 13.61万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2010-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7640794
• 关键词: Algorithms; Bayesian Method; Behavioral; Behavioral Sciences; Cancer Control; Cessation of life; Characteristics; Chronic Disease; Clinic; Computer Hardware; Controlled Study; Data Collection; Development; Devices; Diagnosis; Dimensions; Disease Outcome; Early Diagnosis; Endogenous depression; Fatigue; Goals; Grant; Handheld Computers; Health; Individual; K-Series Research Career Programs; Length; Living Wills; Malignant Neoplasms; Measurement; Measures; Medical; Mentors; Methodology; Methods; Monitor; Moods; Nausea; Outcome; Outcomes Research; Pain; Patient Monitoring; Patient Outcomes Assessments; Patient Self-Report; Patients; Performance; Prevention; Prevention Research; Primary Cancer Prevention; Principal Investigator; Quality of life; Relative (related person); Reporting; Research; Research Personnel; Research Project Grants; Research Proposals; Research Training; Respondent; Scheme; Science; Second Primary Cancers; Simulate; Statistical Methods; Statistical Models; Surveys; Symptoms; Testing; Tilia; Time; Training; United States National Institutes of Health; base; cancer prevention; cancer therapy; career development; computerized; depressed; depression; depressive symptoms; improved; instrument; interest; premature; prevent; response; simulation; tertiary prevention; tool

DESCRIPTION (provided by applicant): My goal is to be a quantitative methodologist focusing in behavioral science applications. Specifically I am interested in using computerized adaptive testing (CAT) to improve longitudinal measurement of patient reported health outcomes important in cancer prevention and cancer control, such as depressive symptoms. In order to get precise measurement of patient-reported health outcomes, self-report surveys tend to be long and create a moderate-to-high level of respondent burden. CAT is a more efficient measurement tool than most current scales and reduces response burden while simultaneously increasing precision. I propose to improve longitudinal assessment by first improving CAT methodology to achieve even higher gains, and then to develop CAT measurement instruments for longitudinal measurement of patient-reported health outcomes. This career development award will build upon my previous training in statistical science and give me further training in cutting edge Bayesian statistical methods and patient reported health outcomes research. I have assembled a mentoring team of two statisticians, a psychometrician, a quality of life researcher, and one of the leaders in developing computerized adaptive tests (CAT) for measuring patient reported health outcomes. My research proposal focuses on developing methodological enhancements to current CAT algorithms, and developing new algorithms to further reduce respondent burden in longitudinal assessments of patient reported health outcomes in behavioral cancer prevention and cancer control studies. I hypothesize that tailoring CAT algorithms to longitudinal assessment will improve precision and reduce patient burden relative to current methods. I will use simulation studies to 1) compare three different methods for developing a CAT algorithm, and 2) to develop and compare CAT algorithms tailored to longitudinal assessment. The research and training in this career development award will prepare me to be a principal investigator on research projects and grants that continue methodological enhancements in CAT used to measure patient reported health outcomes in behavioral cancer prevention and control studies, and to bring this tool into the clinic for research purposes. The methodology developed in this study will be applicable to a wide range of computer hardware devices, such as desktops, laptops, and even handheld computers.

描述（由申请人提供）：我的目标是成为一名专注于行为科学应用的定量方法学家。我特别感兴趣的是使用计算机化自适应测试（CAT）来改善患者报告的健康结果的纵向测量，这些结果对癌症预防和癌症控制很重要，比如抑郁症状。为了精确衡量患者报告的健康结果，自我报告调查往往很长，并造成中度至高度的应答者负担。CAT是一种比目前大多数标度更有效的测量工具，减少了响应负担，同时提高了精度。我建议改进纵向评估，首先改进CAT方法，以获得更高的收益，然后开发CAT测量工具，用于对患者报告的健康结果进行纵向测量。