Large-Scale Online stimulus Norming and Surveys about Perceptions in Healthcare

大规模在线刺激规范和医疗保健认知调查

• 批准号: 10265205
• 负责人: Lauren Atlas
• 金额: $ 3.59万
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10265205
• 关键词: African American; American; Americas; Analgesics; Behavior; Belief; Characteristics; Clinic; Clinical; Competence; Cues; Data; Data Analyses; Data Collection; Environment; Face; Facial Muscles; Female; Geography; Health Care Research; Healthcare; Human; Image; Individual; Judgment; Label; Laboratories; Literature; Measures; Mechanics; Medical; Movement; Operative Surgical Procedures; Pain; Pain Measurement; Pain Threshold; Pain management; Participant; Patients; Perception; Pilot Projects; Population Heterogeneity; Procedures; Process; Protocols documentation; Provider; Publications; Publishing; Race; Recovery; Research; Research Activity; Research Design; Running; Sampling; Series; Sex Differences; Stimulus; Survey Methodology; Surveys; Testing; Visual; Work; base; computer generated; contextual factors; expectation; experience; experimental study; follow-up; impression; insight; interest; male; pain outcome; pain perception; power analysis; sex; socioeconomics; trait

Pain can be modulated by interpersonal processes that support the patient-provider relationship, and contextual factors related to the treatment environment. In this project, we investigate large-scale norms and beliefs about healthcare in America, and how perceptions of people and other visual cues in the treatment environment influence expectations about pain during treatment and about the pain other people feel. This project uses online survey methodologies to measure large scale normed beliefs and expectations from a geographically, ethnically, and socioeconomically diverse population of Americans. The purpose of this project is to investigate healthcare beliefs that may enhance or diminish pain in the clinic, which can be used to design studies in the laboratory to test if manipulating these beliefs can be advantageous for pain outcomes. Data collection for our first protocol on this project began in FY19. Between FY19 and FY20, we collected five samples on the online platform Mechanical Turk to examine how first impressions of medical providers influence expectations of pain during a medical procedure and expectations for post-surgical recovery. Past work has demonstrated that perceptions of medical providers competence influence the experience of pain in the clinic, and that perceptions of medical providers similarity to a patient influence the patients experience of pain in a simulated clinical interaction. In domains outside of healthcare, research has demonstrated that even first impressions of traits such as competence can influence expectations and behavior: for instance, more competent looking politicians are more likely to be elected. Therefore, we were interested in measuring whether peoples perceptions of medical providers influenced their expectations about pain they might experience if that medical provider were to conduct a procedure on them. Participants completed surveys in which they viewed images of peoples faces and were told that they should imagine that the faces were those of potential medical providers who could conduct a procedure on them. They first chose medical providers that they would prefer to conduct painful procedures on them, and then they rated how painful they expected those procedures to be and the types of treatment they would expect that they would need in post-surgical recovery. In two of our samples, we used computer generated faces; in three other samples, we used real human faces. In four of our samples, participants rated how similar the stimulus faces were to themselves. In some samples, participants also rated the faces on perceived competence (in other samples, we used stimuli from published stimulus sets on which these characteristics had already been rated). We observed that people preferred faces that looked more competent and more similar to them to be their medical providers. Furthermore, they expected to experience less pain and to have less need for prescription-strength pain medication following hypothetical procedures conducted by more competent looking medical providers and following procedures conducted by medical providers that were more similar to them. We submitted these results for publication during the summer of FY20 (Necka et al., PsyRxiv) and are currently awaiting reviews. We have also begun data collection on a second series of experiments that evaluates whether individuals perceive pain differently based on the race or sex of a participant. Prior research suggests White individuals need stronger expressions before labeling a face as in pain when viewing the face of a Black actor relative to a White actor. However, these faces differed in identity, were actors, and were all male. We therefore ran a study in which we manipulated the same facial muscle movements (with action units determined based on the pain expression literature) but superimposed these on different identities. Therefore the expressions were identical, it was just the face they were imposed on that differed. We also decided to not only measure potential differences in pain judgments by race, but also by sex, such that female patients and research participants have lower pain tolerance and are less likely to be treated for pain than male patients, similar to the disparities between Black and White individuals regardless of sex. In our first pilot study, we found that individuals were less likely to label the same expression as painful when displayed by a computer-generated female face relative to a male face, regardless of race. We ran power analyses based on these findings and ran a follow up experiment that did not replicate the sex differences, but instead found significant differences based on the race of the face. We are now analyzing these data and plan to run follow up experiments to see whether the race-based differences in pain assessment replicate in a fully powered sample. If so, this has important implications for the perception of pain in African Americans and may provide insights on disparities in pain treatment in the US.

疼痛可以通过支持患者-提供者关系的人际过程以及与治疗环境相关的背景因素来调节。在这个项目中，我们调查了美国有关医疗保健的大规模规范和信念，以及治疗环境中对人的看法和其他视觉线索如何影响对治疗期间疼痛和其他人感受到的疼痛的期望。该项目使用在线调查方法来衡量大规模规范的信念和期望，从地理，种族和社会经济多样化的美国人口。该项目的目的是调查可能增强或减少临床疼痛的医疗保健信念，这些信念可用于设计实验室研究，以测试操纵这些信念是否有利于疼痛结局。 该项目的第一个方案的数据收集始于2019财年。在2019财年至2020财年期间，我们在在线平台Mechanical Turk上收集了五个样本，以研究医疗服务提供者的第一印象如何影响医疗程序期间的疼痛预期和术后恢复预期。 过去的工作表明，医疗服务提供者的能力的看法影响的经验，在诊所的疼痛，和医疗服务提供者的看法相似的病人影响病人的疼痛体验在一个模拟的临床互动。 在医疗保健以外的领域，研究表明，即使是对能力等特征的第一印象也会影响期望和行为：例如，看起来更有能力的政治家更有可能当选。 因此，我们有兴趣测量人们对医疗提供者的看法是否会影响他们对医疗提供者对他们进行手术时可能经历的疼痛的预期。参与者完成了一项调查，在调查中，他们看到了人们的面部图像，并被告知他们应该想象这些面部是那些可以对他们进行手术的潜在医疗提供者。 他们首先选择他们更愿意对他们进行痛苦手术的医疗服务提供者，然后他们评估他们期望这些手术有多痛苦，以及他们期望在手术后恢复中需要的治疗类型。 在我们的两个样本中，我们使用了计算机生成的人脸;在另外三个样本中，我们使用了真实的人脸。 在我们的四个样本中，参与者评估了刺激面孔与自己的相似程度。 在一些样本中，参与者还根据感知能力对面孔进行评级（在其他样本中，我们使用了来自已发布的刺激集的刺激，这些特征已经被评级）。 我们观察到，人们更喜欢那些看起来更有能力、更像他们的人来做他们的医疗服务提供者。此外，他们预计经历更少的疼痛，并有更少的处方强度止痛药的需要后，由更有能力的医疗提供者进行的假设程序和以下程序进行的医疗提供者，更类似于他们。 我们在20财年夏季提交了这些结果以供发表（Necka等人，PsyRxiv），目前正在等待审查。 我们还开始了第二系列实验的数据收集，该实验评估个体是否根据参与者的种族或性别对疼痛有不同的感知。先前的研究表明，相对于白色演员，当看到黑人演员的脸时，白色人需要更强烈的表情才能将一张脸标记为痛苦。只不过这些面孔身份不同，都是演员，而且都是男性。因此，我们进行了一项研究，在这项研究中，我们操纵了相同的面部肌肉运动（根据疼痛表达文献确定的动作单位），但将这些动作叠加在不同的身份上。因此，表情是相同的，只是他们被强加的脸不同。我们还决定不仅按种族测量疼痛判断的潜在差异，还按性别测量，例如女性患者和研究参与者的疼痛耐受性较低，并且与男性患者相比，女性患者和研究参与者接受疼痛治疗的可能性较低，这与黑人和白色个体之间的差异（无论性别如何）相似。在我们的第一个试点研究中，我们发现，无论种族如何，当计算机生成的女性面孔相对于男性面孔显示相同的表情时，个体不太可能将其标记为痛苦。我们根据这些发现进行了功效分析，并进行了一项后续实验，该实验没有复制性别差异，而是根据面部的种族发现了显着差异。我们现在正在分析这些数据，并计划进行后续实验，以确定疼痛评估中基于种族的差异是否会在完全有效的样本中复制。如果是这样的话，这对非洲裔美国人的疼痛感知有重要意义，并可能为美国疼痛治疗的差异提供见解。