Developing a Pain Intensity Measure for Persons with Dementia: Initial Construction and Testing
Developing a Pain Intensity Measure for Persons with Dementia: Initial Construction and Testing
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DOI：
10.1093/pm/pny180
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发表时间：
2019-06-01
期刊：
影响因子：
3.1
通讯作者：
Nelson, Francis X.
中科院分区：
文献类型：
--
作者：
Ersek, Mary;Herr, Keela;Nelson, Francis X.
目标。本研究的目的是确定一组有限的疼痛指标，这些指标最能预测身体疼痛。我们从现有的疼痛观察工具中挑选了140个项目，并使用改进的德尔菲法进行统计分析，以减少项目池。方法。通过德尔菲法，我们创建了一个候选项目集的行为指标。接下来，训练有素的工作人员观察养老院的居民，并根据行为强度和频率对项目进行评分。我们评估了项目之间的关联以及专家临床医生对疼痛强度的评估。设置。阿拉巴马州和宾夕法尼亚州东南部的四家政府拥有的养老院和12家社区养老院。参与者。95名居民（平均年龄= 84.9岁）有中度至重度认知障碍。结果。使用最小绝对收缩和选择算子模型，我们确定了七个项目，最能预测临床医生对疼痛强度的评估。这些项目是僵硬/僵硬的身体或身体部位，支撑，抱怨，表达的眼睛，鬼脸，皱眉和叹息。我们还发现，基于行为频率评级的模型并不比基于行为强度评级的模型具有更好的预测能力。结论。我们使用了两种互补的方法——专家意见和统计分析——将大量的行为指标减少到一组简洁的项目，以预测痴呆症患者的疼痛强度。未来的研究需要检验这个量表的心理测量特性，它被称为痴呆症患者疼痛强度测量。
Objective. The goal of this study was to identify a limited set of pain indicators that were most predicive of physical pain. We began with 140 items culled from existing pain observation tools and used a modified Delphi approach followed by statistical analyses to reduce the item pool. Methods. Through the Delphi Method, we created a candidate item set of behavioral indicators. Next, trained staff observed nursing home residents and rated the items on scales of behavior intensity and frequency. We evaluated associations among the items and expert clinicians' assessment of pain intensity. Setting. Four government-owned nursing homes and 12 community nursing homes in Alabama and Southeastern Pennsylvania. Participants. Ninety-five residents (mean age = 84.9 years) with moderate to severe cognitive impairment. Results. Using the least absolute shrinkage and selection operator model, we identified seven items that best predicted clinicians' evaluations of pain intensity. These items were rigid/stiff body or body parts, bracing, complaining, expressive eyes, grimacing, frowning, and sighing. We also found that a model based on ratings of frequency of behaviors did not have better predictive ability than a model based on ratings of intensity of behaviors. Conclusions. We used two complementary approaches-expert opinion and statistical analysis-to reduce a large pool of behavioral indicators to a parsimonious set of items to predict pain intensity in persons with dementia. Future studies are needed to examine the psychometric properties of this scale, which is called the Pain Intensity Measure for Persons with Dementia.