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

描述(由申请人提供)：拟议的项目旨在调查性别、种族和民族以及年龄对卫生保健提供者关于疼痛治疗的决定的相对贡献。大量的轶事和相关数据表明，男性和女性对不同的疼痛状况接受不同的治疗。同样，在疼痛治疗方面，不同种族群体的治疗也存在差异。已公布的数据和我们的试点研究表明，与年轻患者相比，年龄较大的疼痛患者可能不太可能接受止痛药。这项申请代表着我们的“疼痛感知中的性别与性别”拨款的竞争性更新，该拨款表明，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中性别差异的强大决定因素。我们还证明，这些与性别相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镜头模型方法，通过互联网提供，以捕捉牙医、护士和医生的决策政策，他们将对具有不同疼痛表现的“虚拟人”的多媒体案例小插曲做出决定。透镜模型方法将允许确定个人或群体对疼痛治疗决策的统计可靠预测因素。创新的“虚拟人”网上交付系统将允许招募更大规模的样本，充分代表性别和种族群体，以便对它们之间的差异进行统计分析。通过使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，关于疼痛治疗的决定的系统变异性将是卫生保健提供者在做出关于疼痛的决定时使用性别、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，并测试关于社会学习对提供者治疗决策的影响的具体假设。这项研究解决了在评估和治疗疼痛时需要了解、认识和改变性别、种族和年龄差异的公共卫生需求。这一结果将对治疗和医疗保健专业人员的培训产生直接影响，特别是在评估他们关于疼痛治疗的决定时的性别、种族和年龄。公共卫生相关性：这项研究解决了在疼痛评估和治疗中理解、认识和改变性别、种族和年龄偏见的公共卫生需求。这些结果将对治疗和医疗保健专业人员的培训产生直接影响，特别是在评估他们关于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.