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从慢性病患者群体中收集和分析纵向数据的潜在陷阱。

Potential Pitfalls in Collecting and Analyzing Longitudinal Data from Chronically Ill Populations.

作者信息

Holditch-Davis Diane, Levy Janet

机构信息

Duke University School of Nursing Box 3322 DUMC Durham, NC 27710.

出版信息

Newborn Infant Nurs Rev. 2010 Mar 1;10(1):10-18. doi: 10.1053/j.nainr.2009.12.003.

Abstract

Research on the prevention and management of chronic illnesses involves understanding changes in complex and interrelated aspects of each individual. To capture these changes or to control for them, nursing and health research needs to be longitudinal. However, there are a number of potential pitfalls in analyzing longitudinal data from a chronically ill population. This paper will examine four major pitfalls: selection of time points, measurement, choosing appropriate statistical procedures, and missing values. Although the frequency of data collection is often driven primarily by practical concerns, it will affect the results. In addition, outcome measures may capture different constructs at different points in times. Traditional analysis techniques often have assumptions about data characteristics that are violated in clinical populations. Missing values are common in research with chronically ill individuals because of problems of subject retention and because individuals have frequent medical complications. Solutions to these pitfalls are also discussed.

摘要

慢性病预防与管理的研究涉及了解个体复杂且相互关联的各个方面的变化。为了捕捉这些变化或对其进行控制,护理与健康研究需要具有纵向性。然而,在分析慢性病患者群体的纵向数据时存在一些潜在的陷阱。本文将探讨四个主要陷阱:时间点的选择、测量、选择合适的统计程序以及缺失值。尽管数据收集的频率通常主要由实际问题驱动,但它会影响结果。此外,结局指标在不同时间点可能会捕捉到不同的结构。传统分析技术通常对数据特征有一些假设,而这些假设在临床人群中会被违反。由于受试者留存问题以及个体频繁出现医疗并发症,缺失值在慢性病患者研究中很常见。本文还讨论了针对这些陷阱的解决方法。

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