课题基金 / 基金详情

Development and Evaluation of a Depression Risk Calculator

Development and Evaluation of a Depression Risk Calculator
抑郁症风险计算器的开发和评估
批准号:
8146949
负责人:
Stephen M. Thielke
金额:
$11.45万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-09-23 至 2014-05-31

项目摘要

项目成果

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中文摘要
翻译
描述(申请人提供):数以百万计的老年人患有抑郁症。患者参与有效治疗的一个关键障碍是难以量化抑郁的严重程度和预测未来抑郁度过的时间。更精确的抑郁症风险模型将为患者提供关于他们未来进程的更好信息,并允许更有效地分享决策。我提出了一项为期四年、有指导的研究计划,以开发和评估“抑郁风险计算器”。这一工具将有助于识别有抑郁风险的患者,为他们提供更多关于他们抑郁轨迹的信息,识别与抑郁相关的其他症状,并加强患者和提供者之间的共同决策。为了实现这一目标,我将学习纵向数据分析和定性方法的课程,并获得在初级保健中应用共享决策的经验。使用三个关于老年人的大型纵向数据库(CHS、HRS和Impact),我将为抑郁症风险计算器开发算法。我将征求五名之前接受过抑郁症治疗的患者的意见,了解来自计算器的信息将如何对他们产生最大好处,并将相应地调整输出。然后我将确定抑郁风险计算器的反馈对患者水平结果的影响,特别是患者的参与度和治疗方法的使用。我将从计算器向20名患者提供反馈,并将他们的经历与20名患者的对照组进行比较,跟踪观察一年。这项研究将为使用风险模型改善老年抑郁症治疗的更大规模的研究产生假设和产生初步结果。 公共卫生相关性:数以百万计的老年人患有抑郁症,但对他们和他们的提供者来说,要了解他们的症状有多严重,以及随着时间的推移会发生什么变化,可能是一件具有挑战性的事情。对于其他情况,风险计算器可以确定患者发展和继续患病的可能性,这可以帮助患者和提供者决定最合适的治疗方法。例如,弗雷明翰风险计算器可以在线免费获得,它可以估计个人心脏病发作的风险,并可以帮助患者和提供者做出决定。我计划通过使用四项大型研究的数据,对老年人进行长期调查,开发一个抑郁风险计算器,它将(1)预测患者未来可能度过的抑郁时间,(2)确定可能导致抑郁的相关因素,以及(3)估计治疗对未来病程的影响。我将评估来自这样一个计算器的反馈将如何帮助老年人和他们的提供者改善抑郁症的知识、决策和治疗方法的使用。
英文摘要
DESCRIPTION (provided by applicant): Millions of older adults suffer from depression. A key barrier to patient engagement in application of effective treatments is the difficulty in quantifying depression severity and anticipating future time spent depressed. More refined models of depression risk would give patients better information about their future course, and allow more effective shared decision making. I propose a four-year, mentored research plan to develop and evaluate a "depression risk calculator". This tool will be useful for identifying patients at risk for depression, giving them more information about their depression trajectory, identifying other symptoms associated with depression, and enhancing shared decision making between patients and providers. In order to accomplish this end, I will take courses in longitudinal data analysis and qualitative methods, and gain experience in applying shared decision making in primary care. Using three large longitudinal databases of older adults (CHS, HRS, and IMPACT) I will develop algorithms for a depression risk calculator. I will seek input from five patients previously treated for depression about how information from the calculator would have the most benefit for them, and will tailor the outputs accordingly. I will then ascertain the effects of feedback from a depression risk calculator on patient-level outcomes, particularly patient engagement and use of treatments. I will provide feedback from the calculator to 20 patients, and compare their experiences with those of a control group of 20 patients, followed for one year. This research will generate hypotheses and produce preliminary results for larger studies of using risk models to improve treatment for geriatric depression. PUBLIC HEALTH RELEVANCE: Millions of older adults suffer from depression, but it can be challenging for them and their providers to appreciate how severe their symptoms are, and how they will change over time. For other conditions, risk calculators can identify a patient's likelihood of developing and continuing in a disease, which can help patients and providers to decide on the most fitting treatments. For example, the Framingham risk calculator, which is freely available on-line, estimates an individual's risk of having a heart attack, and can assist patients and providers in making decisions. I plan, by using data from four large studies which surveyed older adults over long periods of time, to develop a depression risk calculator, which will (1) project the amount of time a patient is likely to spend depressed in the future, (2) identify the related factors that may be contributing to depression, and (3) estimate the effects of treatments on future course. I will assess how feedback from such a calculator would help older adults and their providers to improve knowledge, decisions, and use of treatments for depression.
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