Massof Robert W
Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
J Appl Meas. 2010;11(3):253-70.
Comparative effectiveness research in rehabilitation medicine requires the development and validation of clinically meaningful and scientifically rigorous measurements of patient states and theories that explain and predict outcomes of intervention. Patient traits are latent (unobservable) variables that can be measured only by inference from observations of surrogate manifest (observable) variables. In the behavioral sciences, latent variables are analogous to intensive physical variables such as temperature and manifest variables are analogous to extensive physical variables such as distance. Although only one variable at a time can be measured, the variable can have a multidimensional structure that must be understood in order to explain disagreements among different measures of the same variable. The use of Rasch theory to measure latent trait variables can be illustrated with a balance scale metaphor that has randomly added variability in the weights of the objects being measured. Knowledge of the distribution of the randomly added variability provides the theoretical structure for estimating measures from ordinal observation scores (e.g., performance measures or rating scales) using statistical inference. In rehabilitation medicine, the latent variable of primary interest is the patient's functional ability. Functional ability can be estimated from observations of surrogate performance measures (e.g., speed and accuracy) or self-report of the difficulty the patient experiences performing specific activities. A theoretical framework borrowed from project management, called the Activity Breakdown Structure (ABS), guides the choice of activities for assessment, based on the patient's value judgments, to make the observations clinically meaningful. In the case of low vision, the functional ability measure estimated from Rasch analysis of activity difficulty ratings was discovered to be a two-dimensional variable. The two visual function dimensions are independent of physical limitations and psychological state. To explain outcome measures (latent variable estimated from difficulty ratings), a theory must be developed that explicitly defines how latent variables are related to the observed manifest variables and to each other. The latent variables are categorized as primary variables, which in the case of low vision are the two visual function dimensions, and as effect modifiers, which in the case of low vision are other physical and psychological latent traits of the patients that can influence the outcome measures. Interventions give rise to latent intervention effect variables that can alter the latent primary variables or independently affect the outcome measures. The latent effect modifier variables, in turn, can alter the latent intervention effect variables. Once developed and validated, a theory of this form will predict the rehabilitation potential of individual patients, i.e., the probability of obtaining criterion outcome measures given the observed state of the patient and the choice of interventions.
康复医学中的比较效果研究需要开发并验证对患者状态进行具有临床意义且科学严谨的测量方法，以及能够解释和预测干预结果的理论。患者特征是潜在（不可观察）变量，只能通过对替代的显性（可观察）变量的观察进行推断来测量。在行为科学中，潜在变量类似于诸如温度等强度物理变量，而显性变量类似于诸如距离等广延物理变量。虽然一次只能测量一个变量，但该变量可能具有多维结构，为了解释同一变量不同测量之间的差异，必须对其加以理解。使用拉施理论测量潜在特质变量可以用一个天平隐喻来说明，天平在被测量物体的重量上随机增加了变异性。了解随机增加的变异性的分布情况，为使用统计推断从顺序观察分数（如表现测量或评定量表）估计测量值提供了理论结构。在康复医学中，主要关注的潜在变量是患者的功能能力。功能能力可以从替代表现测量（如速度和准确性）的观察结果或患者对执行特定活动所经历困难的自我报告中进行估计。一个从项目管理中借鉴的理论框架，称为活动分解结构（ABS），基于患者的价值判断指导评估活动的选择，以使观察结果具有临床意义。在低视力的情况下，通过对活动难度评级的拉施分析估计的功能能力测量值被发现是一个二维变量。这两个视觉功能维度独立于身体限制和心理状态。为了解释结果测量（从难度评级估计的潜在变量），必须开发一种理论，明确界定潜在变量如何与观察到的显性变量以及彼此之间相关联。潜在变量被分类为主要变量，在低视力的情况下是两个视觉功能维度，以及效应修饰变量，在低视力的情况下是患者的其他身体和心理潜在特质，它们可以影响结果测量。干预会产生潜在的干预效应变量，这些变量可以改变潜在的主要变量或独立影响结果测量。反过来，潜在的效应修饰变量可以改变潜在的干预效应变量。一旦这种形式的理论得到开发和验证，它将预测个体患者的康复潜力，即根据患者的观察状态和干预选择获得标准结果测量的概率。
