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: 10006680
• 负责人: Lauren Atlas
• 金额: $ 0.99万
• 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/10006680
• 关键词: American; Americas; Analgesics; Attitude; Behavior; Belief; Characteristics; Clinic; Clinical; Competence; Cues; Data; Data Collection; Environment; Face; Geography; Health Care Research; Healthcare; Human; Image; Laboratories; Manuscripts; Measures; Mechanics; Medical; Operative Surgical Procedures; Pain; Pain management; Participant; Patients; Perception; Population Heterogeneity; Procedures; Process; Provider; Publications; Publishing; Race; Recovery; Research Activity; Research Design; Role; Sampling; Stimulus; Survey Methodology; Surveys; Testing; Visual; Work; Writing; computer generated; contextual factors; expectation; experience; impression; interest; pain outcome; 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 this project began in FY19. We began by asking 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. We were also interested in whether their beliefs about medical providers and pain treatment options in general (i.e., medical providers in general are competent, I feel favorable about herbal medication for pain) would influence their expectations. In FY2019, we collected four samples on the online platform Mechanical Turk to test this question. 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 two other samples, we used real human faces. In three 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 are now exploring the role of their attitudes on their pain and treatment expectations, and are exploring the role of hypothetical provider demographic characteristics (e.g., race/sex) on participants expectations. We are also in the process of writing up a manuscript for publication explaining the effects of first impressions of provider competence and similarity on pain and treatment expectations.

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。该项目的数据收集始于2019财年。我们首先询问医疗提供者的第一印象如何影响医疗过程中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。我们还感兴趣的是他们对医疗提供者和疼痛治疗选择的信念（即，医疗提供者一般都有能力，我对草药治疗疼痛感到满意）会影响他们的期望。 于2019财政年度，我们于网上平台Mechanical Turk收集四个样本以测试此问题。 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;在另外两个样本中，我们使用了真实的人脸。 在我们的三个样本中，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。 我们现在正在探索他们的态度对他们的疼痛和治疗期望的作用，并正在探索假设的提供者人口统计特征的作用（例如，种族/性别）对参与者的期望。我们还在撰写一份手稿以供出版，解释提供者能力和相似性对疼痛和治疗期望的第一印象的影响。