Pain Treatment Decisions: Influence of Sex, Race, and Age

拟议的项目旨在调查性别、种族的相对贡献。 以及种族和年龄对医疗保健提供者关于疼痛治疗的决定。 大量的轶事和相关数据表明，男性和女性 针对不同的疼痛情况采取不同的治疗方法。同样，也存在着差距。 在疼痛治疗方面，不同种族群体的治疗。我们的初步研究已经 研究表明，与老年患者相比，老年患者接受止痛药的可能性较小 更年轻的病人。这个应用程序代表着我们的“性与性别”的竞争性更新 在疼痛感知方面“拨款表明，社会学习，特别是与性别有关的学习 对疼痛的刻板印象和期望是性行为的强大决定因素 疼痛反应的差异。我们还证明了这些与性别相关的 期望值影响了对他人痛苦的感知。我们建议聘请一名 创新的镜头模型方法，通过互联网提供，以捕捉决策 将对多媒体做出决定的牙医、护士和医生的政策 “虚拟人”的案例小插曲，呈现了不同的痛苦。镜头 模型方法将允许确定个人或群体的 统计上可靠的疼痛治疗决定的预测者。基于Web的 交付系统将允许招募更大规模的样本，并具有足够的 性别和种族群体的代表性，用于统计分析 他们。通过使用面部表情编码系统，我们将能够标准化 不同性别和种族的疼痛表达程度。决策的系统性可变性 因此，疼痛治疗将是医疗保健提供者的偏见和 期望值。这一方法论将允许审查 这些关键变量和关于社会学习影响的特定假设的检验 提供者的治疗决定。这项研究解决了公共卫生需要 了解、认识和改变评估中的性别、种族和年龄偏见 以及疼痛的治疗。结果将对治疗和治疗产生直接影响 培训保健专业人员，特别是在性别评估方面， 在他们关于疼痛治疗的决定中，种族和年龄存在偏见。

The proposed project is designed to investigate the relative contributions of gender, race and ethnicity, and age to health care providers decisions about pain treatment. Considerable anecdotal and correlational data suggest that men and women receive different treatment for a variety of pain conditions. Similarly, there are disparities in the treatment of different racial groups with respect to pain treatment. Our pilot research has shown that older pain sufferers may be less likely to receive pain medication compared to younger patients. The application represents a competing renewal of our "Sex vs. Gender in Pain Perception" grant which demonstrated that social learning, particularly genderrelated stereotypes and expectations about pain were powerful determinants of sex differences in pain responding. We also demonstrated that these gender-related expectations influenced the perception of others' pain. We propose to employ an innovative LENS model approach, delivered via the internet, to capture the decision policies of dentists, nurses, and physicians who will make decisions about multimedia case vignettes of "Virtual Humans" with different presentations of pain. The LENS model methodology will allow for the determination of an individual's or group's statistically reliable predictors of the decisions about pain treatment. The Web-based delivery system will allow for the recruitment of larger sample sizes with sufficient representation of sexes, and racial groups for statistical analyses of differences between them. By employing a facial expression coding system we will be able to standardize the degree of pain expression across gender and race. Systematic variability in decisions about pain treatment will therefore be a function of the health care provider's biases and expectations. This methodology will allow for an examination of the contribution of these key variables and tests of specific hypotheses about social learning influences on provider's treatment decisions. The research addresses the public health need to understand, recognize and change gender, race, and age biases in the assessment and treatment of pain. The results will have direct implications for treatment and the training of health care professionals, particularly in the assessment of gender, race, and age biases in their decisions about pain treatment.