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虚拟人类技术:在个体疼痛决策策略中捕捉性别、种族和年龄的影响。

Virtual human technology: capturing sex, race, and age influences in individual pain decision policies.

作者信息

Hirsh Adam T, Alqudah Ashraf F, Stutts Lauren A, Robinson Michael E

机构信息

Center for Pain Research and Behavioral Health, University of Florida, P.O. Box 100165, Gainesville, FL 32610-0165, USA Department of Psychology, University of Jordan, Amman, Jordan.

出版信息

Pain. 2008 Nov 15;140(1):231-238. doi: 10.1016/j.pain.2008.09.010. Epub 2008 Oct 18.

DOI:10.1016/j.pain.2008.09.010
PMID:18930596
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2586418/
Abstract

Pain assessment is subject to bias due to characteristics of the individual in pain and of the observing person. Few research studies have examined pain assessment biases in an experimental setting. This study employs innovative virtual human technology to achieve greater experimental control. A lens model design was used to capture decision-making policies at the idiographic and nomothetic level. Seventy-five undergraduates viewed virtual humans (VH) that varied in sex, race, age, and pain expression. Participants provided computerized ratings with Visual Analogue Scales on the VH's pain intensity, pain unpleasantness, negative mood, coping, and need for medical treatment. Idiographic analyses revealed that individuals used pain expression most frequently as a significant cue. Nomothetic analyses showed that higher pain expression VH and female VH were viewed as having higher pain intensity, higher pain unpleasantness, greater negative mood, worse coping, and a greater need to seek medical treatment than lower pain expression VH and male VH, respectively. Older VH were viewed as having worse coping and a greater need to seek medical treatment than younger VH. This innovative paradigm involving VH technology and a lens model design was shown to be highly effective and could serve as a model for future studies investigating pain-related decision making in healthcare providers.

摘要

由于处于疼痛中的个体以及观察人员的特征,疼痛评估容易受到偏差影响。很少有研究在实验环境中检验疼痛评估偏差。本研究采用创新的虚拟人技术以实现更好的实验控制。采用透镜模型设计来获取个体层面和普遍层面的决策策略。75名本科生观看了在性别、种族、年龄和疼痛表现方面存在差异的虚拟人。参与者通过视觉模拟量表对虚拟人的疼痛强度、疼痛不适感、负面情绪、应对方式以及医疗需求进行计算机化评分。个体层面分析显示,个体最常将疼痛表现用作重要线索。普遍层面分析表明,与疼痛表现较低的虚拟人和男性虚拟人相比,疼痛表现较高的虚拟人和女性虚拟人分别被视为具有更高的疼痛强度、更高的疼痛不适感、更强烈的负面情绪、更差的应对方式以及更大的就医需求。与年轻虚拟人相比,年长虚拟人被视为具有更差的应对方式和更大的就医需求。这种涉及虚拟人技术和透镜模型设计的创新范式被证明是非常有效的,并且可以作为未来研究医疗保健提供者中与疼痛相关决策的模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dcbc/2586418/5dc20becc6f3/nihms78971f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dcbc/2586418/5c868b703760/nihms78971f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dcbc/2586418/5dc20becc6f3/nihms78971f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dcbc/2586418/5c868b703760/nihms78971f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dcbc/2586418/5dc20becc6f3/nihms78971f2.jpg

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