Development of a Composite Pain Measure for Persons with Advanced Dementia: Exploratory Analyses in Self-Reporting Nursing Home Residents
Development of a Composite Pain Measure for Persons with Advanced Dementia: Exploratory Analyses in Self-Reporting Nursing Home Residents
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DOI：
10.1016/j.jpainsymman.2010.06.009
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发表时间：
2011-03-01
影响因子：
4.7
通讯作者：
Neradilek, Moni Blazej
中科院分区：
文献类型：
--
作者：
Ersek, Mary;Polissar, Nayak;Neradilek, Moni Blazej
上下文。专家一致认为，不与人交流的人的疼痛评估需要来自不依赖自我报告的来源的数据，包括代理报告、健康史和对疼痛行为的观察。然而，几乎没有经验证据来指导临床医生对这些来源进行加权或组合，以最好地接近个人的经验。这项探索性研究的目的是确定一组依赖观察者的疼痛指标的组合，这些指标比任何单一指标对自我报告的疼痛强度的预测性要强得多。由于自述疼痛通常被视为衡量疼痛的标准，因此自述通常疼痛和最严重疼痛是因变量。样本包括居住在24家养老院之一的326名居民(平均年龄：83.2岁；69%为女性)。自变量不依赖于自我报告：使用爱荷华州疼痛温度计(IPT)、非语言疼痛指标(CNPI)、康奈尔痴呆症抑郁量表(CSDD)、匹兹堡激动量表(PAS)、痛苦诊断次数和最小数据集(MDS)疼痛变量的认证护士助理(CNA)的代理报告。在单变量分析中，CNA IPT评分与自我报告的疼痛的相关性最高。自我报告的常见疼痛的最终多变量模型包括CNA、IPT、CSDD、PAS和教育；该模型仅解释了14%的变量。最终的两个最严重疼痛模型中，MDS疼痛频率、CSDD、CNA IPT、CNPI和年龄更广泛(R-2=0.14)。还需要进一步的研究来为非语言人士开发一个可预测的疼痛模型。J疼痛症状管理2011；41：566-579。(C)2011年美国癌症疼痛缓解委员会。爱思唯尔公司出版，版权所有。
Context. Experts agree that pain assessment in noncommunicative persons requires data from sources that do not rely on self-report, including proxy reports, health history, and observation of pain behaviors. However, there is little empirical evidence to guide clinicians in weighting or combining these sources to best approximate the person's experience.Objectives. The aim of this exploratory study was to identify a combination of observer-dependent pain indicators that would be significantly more predictive of self-reported pain intensity than any single indicator. Because self-reported pain is usually viewed as the criterion measure for pain, self-reported usual and worst pains were the dependent variables.Methods. The sample consisted of 326 residents (mean age: 83.2 years; 69% female) living in one of 24 nursing homes. Independent variables did not rely on self-report: surrogate reports from certified nursing assistants (CNAs) using the Iowa Pain Thermometer (IPT), Checklist of Nonverbal Pain Indicators (CNPI), Cornell Scale for Depression in Dementia (CSDD), Pittsburgh Agitation Scale (PAS), number of painful diagnoses, and Minimum Data Set (MDS) pain variables.Results. In univariate analyses, the CNA IPT scores were correlated most highly with self-reported pain. The final multivariate model for self-reported usual pain included CNA IPT, CSDD, PAS, and education; this model accounted for only 14% of the variance. The more extensive of the two final models for worst pain included MDS pain frequency, CSDD, CNA IPT, CNPI, and age (R-2 = 0.14).Conclusion. Additional research is needed to develop a predictive pain model for nonverbal persons. J Pain Symptom Manage 2011; 41: 566-579. (C) 2011 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.