Innovative pain outcomes derived from patients real-time pain reports

来自患者实时疼痛报告的创新疼痛结果

• 批准号: 9102902
• 负责人: Stefan Schneider
• 金额: $ 57.33万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9102902
• 关键词: Affect; Behavioral Research; Cereals; Characteristics; Classification; Clinical; Clinical Research; Clinical Trials; Data; Data Analyses; Data Collection; Data Set; Development; Diagnostic; Ecological momentary assessment; Environment; Etiology; Evaluation; Frequencies; Generations; Goals; Health; Health Personnel; Intervention; Knowledge; Life; Light; Measurement; Measures; Medical Research; Outcome; Outcome Measure; Pain; Pain Disorder; Pain Measurement; Pain Research; Pain intensity; Pain interference; Patient Outcomes Assessments; Patient Self-Report; Patients; Pattern; Pharmacologic Substance; Physical Function; Process; Property; Psychometrics; Public Health; Publishing; Reporting; Research; Research Personnel; Resolution; Rest; Sample Size; Staging; Testing; Time; Validity and Reliability; base; chronic pain; cost efficient; evidence base; experience; impression; improved; improved outcome; indexing; individualized medicine; innovation; insight; neglect; novel; primary outcome; study characteristics; treatment effect; treatment response

 DESCRIPTION (provided by applicant): Self-reports of pain intensity are indispensable for understanding patients' health and for evaluating core outcomes in clinical trials. Recent methodological advances using real-time pain measurement (Ecological Momentary Assessment) have made it possible to capture patients' pain experiences with high resolution. This has the potential to improve outcomes for behavioral and medical research by considering temporal aspects and environmental correlates of pain intensity. However, to date, outcome measures created from momentary data have generally been limited to the average level of pain intensity. In the proposed research we will examine the utility and validity of an expanded set of pain indices derived from patients' momentary pain intensity reports and will determine which are most relevant to stakeholders. There are two broad stages in the proposed research plan. First, we will capture stakeholders' (patients, healthcare providers, regulators, clinical trialist) impressions of the momentary pain patterns that are most important to them; this will form the basis for creating additional pain indices that could improve understanding of treatment effects and provide richer insight into clinical outcomes. Second, the psychometric properties of the new indices will be thoroughly examined in extensive secondary data analyses of many existing momentary pain datasets from academic studies and pharmaceutical trials. These analyses will provide a comprehensive evaluation of the reliability, validity, and sensitivity of the indices, as well as their relationships with other key outcomes in pain clinical research. Results will be synthesized across studies using meta-analytic principles to evaluate their robustness and generalizability across measurement and study characteristics. Novel indices of pain status derived from real-time assessments will refine pain measurement for researchers trying to understand the determinants of pain and developing interventions for pain. Such information has the potential to (1) advance knowledge about etiology, (2) facilitate diagnostic classification of pain conditions, (3) provide new information about patients' pain that could be used to tailor treatments, and (4) augment understanding of the effects of pain interventions.

 描述(由申请人提供)：在临床试验中，疼痛强度的自我报告对于了解患者的健康和评估核心结果是必不可少的。使用实时疼痛测量(生态瞬时评估)的最新方法进步使以高分辨率捕捉患者的疼痛体验成为可能。这有可能通过考虑疼痛强度的时间因素和环境因素来改善行为和医学研究的结果。然而，到目前为止，根据瞬时数据创建的结果测量通常仅限于疼痛强度的平均水平。在拟议的研究中，我们将检查从患者的瞬时疼痛强度报告中得出的一组扩展的疼痛指数的实用性和有效性，并将确定哪些与利益相关者最相关。拟议的研究计划分为两个大的阶段。首先，我们将捕捉利益相关者(患者、医疗保健提供者、监管者、临床试验者)对他们最重要的瞬时疼痛模式的印象；这将形成创建额外疼痛指数的基础，这些指数可以提高对治疗效果的理解，并提供对临床结果的更丰富的洞察。其次，新指数的心理测量学特性将通过对学术研究和药物试验中现有的许多瞬时疼痛数据集进行广泛的二级数据分析来彻底检验。这些分析将提供对指数的可靠性、有效性和敏感性的全面评估，如 以及它们与疼痛临床研究中其他关键结果的关系。研究结果将使用荟萃分析原理进行综合，以评估其在测量和研究特征上的稳健性和普适性。从实时评估中得出的新的疼痛状态指数将为试图了解疼痛的决定因素和开发疼痛干预措施的研究人员改进疼痛测量。这样的信息有可能(1)提高关于病因学的知识，(2)促进诊断分类 (3)提供关于患者疼痛的新信息，可用于量身定做治疗，以及(4)加强对疼痛干预效果的理解。