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

描述（由申请人提供）：拟议项目旨在调查性别、种族和民族以及年龄对医疗保健提供者关于疼痛治疗决策的相对贡献。相当多的轶事和相关数据表明，男性和女性接受不同的治疗各种疼痛条件。同样，不同种族群体在疼痛治疗方面也存在差异。已发表的数据和我们的试点研究表明，与年轻患者相比，老年疼痛患者接受止痛药的可能性较小。该应用程序代表了我们的“性别与性别疼痛感知”补助金的竞争性更新，该补助金表明，社会学习，特别是与性别相关的刻板印象和对疼痛的期望是疼痛反应性别差异的强大决定因素。我们还证明了这些与性别有关的期望影响了对他人痛苦的感知。我们建议采用一种创新的透镜模型方法，通过互联网提供，捕捉决策政策的牙医，护士和医生，他们将作出决定的多媒体情况下的小插曲的“虚拟人”与不同的介绍疼痛。透镜模型方法将允许确定个人或群体的疼痛治疗决策的统计学可靠预测因素。这一创新的“虚拟人”网上提供系统将允许招募更大规模的样本，并有足够的性别和种族群体代表，以便对它们之间的差异进行统计分析。通过采用面部表情编码系统，我们将能够标准化不同性别、年龄和种族的疼痛表达程度。因此，疼痛治疗决策的系统变异性将是医疗保健提供者在做出疼痛决策时使用性别、种族和年龄线索的倾向的函数。这种方法将允许检查这些关键变量的贡献和测试的具体假设社会学习的影响提供者的治疗决定。该研究解决了公共卫生需要了解，认识和改变性别，种族和年龄差异的评估和治疗疼痛。研究结果将对治疗和医疗保健专业人员的培训产生直接影响，特别是在评估性别，种族和年龄方面，他们决定疼痛治疗。公共卫生相关性：该研究解决了公共卫生需要了解，认识和改变性别，种族和年龄偏见的评估和治疗疼痛。研究结果将对治疗和医疗保健专业人员的培训产生直接影响，特别是在评估他们对疼痛治疗的决定中的性别，种族和年龄偏见方面。

DESCRIPTION (provided by applicant): 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. Published data and our pilot research have 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 gender-related 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 innovative, "Virtual Human", 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, age, and race. Systematic variability in decisions about pain treatment will therefore be a function of the health care provider's predisposition to use sex, race, and age cues in making decisions about pain. 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 disparities 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 in their decisions about pain treatment. PUBLIC HEALTH RELEVANCE: 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.