Evaluating the Psychometric Properties of a Pain Assessment Battery for Cerebral Palsy

项目总结 关于测量工具的关键心理测量学特性，我们的知识有一个严重的缺口 我们用来评估重度脑性瘫痪(CP)的慢性疼痛，特别是在反复发作的情况下 对临床程序的评估和表现。如果精准医学要成为一种 认知、沟通和运动障碍与严重形式的脑瘫相关的现实 (以下简称“严重CP”)，还有大量的基础性工作要做。长期目标是 建立一个可靠的“疼痛表型”模型，在临床上与患者的治疗决策相关 有CP。该应用程序的总体目标是建立一组评估(即，疼痛评估 对于患有严重脑瘫的患者是可行的，并且表现出很强的心理测量能力 属性。心理测量学的核心假设是疼痛评估分数将在 时间，将一起变化，并将显著减少后疼痛治疗。这一假设一直是 根据调查小组收集的初步数据制定的。其基本原理是测试分数 与疼痛评估电池的一致性(可靠性)和对变化的敏感度相关的属性为 对于定义痛点至关重要。研究假设将通过完成三个具体目标来检验：1) 确定反复抽样的疼痛测量是否产生心理测量学上的合理分数；2)确定 疼痛测量是否对假定的疼痛治疗反应的变化敏感；以及3)确定数据 目标1中预测疼痛变异性的要素在目标2中评估。为了实现目标，疼痛将是 反复评估之前和之后皮质类固醇关节注射以减轻慢性关节疼痛。 评估包括照顾者对疼痛和心理社会因素的报告，盲目观察编码的疼痛 在标准化的疼痛检查过程中对行为进行评分，以及修改后的量化 体感测试。前两个目标将建立时间和内部的一致性，并会聚和 构建效度。目标3将通过进行回归分析来完成，以确定以下数据元素 可以预测治疗的可变性。拟议的研究具有创新性，因为它利用了复杂的统计方法 建模以同时捕捉疼痛的多维方面(即，强度、干扰、持续时间)， 提供项目级参数校准和潜在特质估计，产生多维因素 结构，并允许有意义地检测个体内部的更改。新的研究可能性是 预计将作为结果提供。建议的贡献是关键心理测量学的文档。 用于重症CP的疼痛评估组件的特性。这一贡献将是重大的，因为它 将为该领域提供可靠的止痛措施，以进一步探索治疗效果和 治疗反应的个体差异。最终，这样的知识会导致疼痛的发展 CP的表型，并支持个体化用药方法。

PROJECT SUMMARY There is a critical gap in our knowledge pertaining to the key psychometric properties of the measurement tools we use to assess chronic pain in severe cerebral palsy (CP), especially in the context of repeated assessments and performance in response to clinical procedures. If precision medicine is ever to become a reality for those with cognitive, communicative and motor impairments associated with severe forms of CP (hereafter `severe CP'), there is a great deal of foundational work yet to be done. The long-term goal is to create a reliable `pain phenotype' model that is clinically relevant to making treatment decisions for patients with CP. The overall objective in this application is to establish a set of assessments (i.e., pain assessment battery) that are feasible for use with patients with severe CP, and that demonstrate strong psychometric properties. The central psychometric hypothesis is that pain assessment scores will be adequately stable over time, will vary together, and will significantly decrease following pain treatment. This hypothesis has been formulated based on preliminary data collected by the investigative team. The rationale is that testing the score properties related to consistency (reliability) and sensitivity to change of the pain assessment battery are essential to defining pain endpoints. The study hypothesis will be tested by completing three specific aims: 1) determine whether pain measures, repeatedly sampled, produce psychometrically sound scores; 2) determine whether the pain measures are sensitive to change in response to putative pain treatment; and 3) identify data elements in Aim 1 that predict pain variability assessed in Aim 2. To accomplish the aims, pain will be repeatedly assessed prior to and again following corticosteroid joint injection to reduce chronic joint pain. Assessments include caregiver report of pain and psychosocial factors, blind observationally coded pain behaviors scored during a standardized pain examination procedure, and a modified quantitative somatosensory test. The first two aims will establish temporal and internal consistency, and convergent and construct validity. Aim 3 will be completed by conducting regression analyses to identify data elements that may predict treatment variability. The proposed research is innovative because it leverages complex statistical modeling to simultaneously capture the multidimensional aspects of pain (i.e., intensity, interference, duration), provides item-level parameter calibrations and latent trait estimates, results in multidimensional factor structures, and allows for meaningful detection of intra-individual change. New research possibilities are expected to become available as a result. The proposed contribution is the documentation of key psychometric properties of the pain assessment battery for use in severe CP. This contribution will be significant because it will position the field with dependable pain measures with which to further explore treatment efficacy and individual differences in treatment response. Ultimately, such knowledge will lead to development of a pain phenotype for CP and support an individualized medicine approach.