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

评估脑瘫疼痛评估组的心理测量特性

基本信息

批准号：
9902481
负责人：
Chantel Courtney Burkitt
金额：
$ 14.05万
依托单位：
GILLETTE CHILDREN'S SPECIALTY HEALTHCARE
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-04-01 至 2022-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9902481
关键词：
Address Adrenal Cortex Hormones Adult Algorithms Analgesics Arthralgia Blinded Botulinum Toxins Calibration Caregivers Cerebral Palsy Characteristics Chronic Clinical Clinical Trials Code Cognitive Communication impairment Complex Data Data Element Detection Development Discipline Documentation Enrollment Family Foundations Frustration Future Goals Health Care Costs Impairment Individual Individual Differences Injections Joints Knowledge Lead Measurement Measures Medical Methods Mission Modeling Motor Opioid Orthopedic Surgery procedures Outcome Pain Pain Measurement Pain intensity Pain interference Pain management Patient Self-Report Patients Performance Phenotype Physical therapy Population Positioning Attribute Postoperative Pain Procedures Property Provider Proxy Psychometrics Psychosocial Factor Public Health Regression Analysis Rehabilitation therapy Reporting Research Sampling Standardization Statistical Models Structure Testing Time Traction Treatment Efficacy United States National Institutes of Health Walking Work base blind chronic pain clinically relevant design disability experience individual variation individualized medicine innovation motor impairment negative affect pain behavior pain model pain outcome pain reduction pain score painful neuropathy precision medicine response somatosensory sound success tool trait treatment response

项目摘要

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.

项目摘要在我们对测量工具的关键心理测量特性的了解方面存在着严重的差距我们用来评估严重脑瘫（CP）的慢性疼痛，特别是在反复发作的情况下，评估和性能，以应对临床程序。如果精准医疗要成为对于那些与严重形式的CP相关的认知，沟通和运动障碍的人来说，（以下简称“严重CP”），还有大量的基础工作要做。长期目标是创建一个可靠的“疼痛表型”模型，该模型与为患者做出治疗决策的临床相关性在CP。本申请的总体目标是建立一组评估（即，疼痛评估电池），可用于严重CP患者，并表现出强大的心理测量特性.中心心理测量学假设是，疼痛评估评分将足够稳定，时间，会一起变化，并且在疼痛治疗后会显着减少。这一假设一直被根据调查小组收集的初步数据拟订。基本原理是测试分数与疼痛评估组合的一致性（可靠性）和变化敏感性相关的属性是对于定义疼痛终点至关重要。研究假设将通过完成三个具体目标进行检验：1）确定是否疼痛措施，重复采样，产生心理测量的声音分数; 2）确定疼痛测量是否对响应于假定疼痛治疗的变化敏感;以及3）识别数据目标1中预测目标2中评估的疼痛变异性的元素。为了实现目标，痛苦将是在皮质类固醇关节注射之前和之后反复评估，以减轻慢性关节疼痛。评估包括护理人员报告的疼痛和心理社会因素，盲法观察编码疼痛在标准化疼痛检查程序中评分的行为，以及修改的定量体感测试前两个目标将建立时间和内部的一致性，结构效度目标3将通过进行回归分析来识别数据元素来完成，可以预测治疗的可变性。拟议的研究是创新的，因为它利用了复杂的统计建模以同时捕获疼痛的多维方面（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，结构，并允许有意义的检测个体内的变化。新的研究可能性是预计将因此而变得可用。拟议的贡献是关键的心理测量文件用于重度CP的疼痛评估组合的特性。这一贡献将是巨大的，因为它将定位领域与可靠的疼痛措施，以进一步探索治疗效果，治疗反应的个体差异。最终，这样的知识会导致一种痛苦的发展表型的CP和支持个性化的医疗方法。